Moved Drivetrain from y2017 python to frc971
Change-Id: If931cf988d2615acc286d288fc0e5c9e7e3a5b90
diff --git a/frc971/control_loops/python/BUILD b/frc971/control_loops/python/BUILD
index b1897e0..4b25bb4 100644
--- a/frc971/control_loops/python/BUILD
+++ b/frc971/control_loops/python/BUILD
@@ -40,3 +40,27 @@
],
restricted_to = ['//tools:k8'],
)
+
+py_library(
+ name = 'drivetrain',
+ srcs = [
+ 'drivetrain.py',
+ ],
+ deps = [
+ ':controls',
+ ],
+ restricted_to = ['//tools:k8'],
+)
+
+py_library(
+ name = 'polydrivetrain',
+ srcs = [
+ 'polydrivetrain.py',
+ ],
+ deps = [
+ ':controls',
+ ':drivetrain',
+ '//external:python-glog',
+ ],
+ restricted_to = ['//tools:k8'],
+)
diff --git a/frc971/control_loops/python/control_loop.py b/frc971/control_loops/python/control_loop.py
index 805e079..900c06f 100644
--- a/frc971/control_loops/python/control_loop.py
+++ b/frc971/control_loops/python/control_loop.py
@@ -475,3 +475,21 @@
self.P = self.Q_steady_state
else:
self.P = numpy.matrix(numpy.zeros((self.A.shape[0], self.A.shape[0])))
+
+
+class CIM(object):
+ def __init__(self):
+ # Stall Torque in N m
+ self.stall_torque = 2.42
+ # Stall Current in Amps
+ self.stall_current = 133.0
+ # Free Speed in rad/s
+ self.free_speed = 5500.0 / 60.0 * 2.0 * numpy.pi
+ # Free Current in Amps
+ self.free_current = 4.7
+ # Resistance of the motor
+ self.resistance = 12.0 / self.stall_current
+ # Motor velocity constant
+ self.Kv = (self.free_speed / (12.0 - self.resistance * self.free_current))
+ # Torque constant
+ self.Kt = self.stall_torque / self.stall_current
diff --git a/frc971/control_loops/python/drivetrain.py b/frc971/control_loops/python/drivetrain.py
new file mode 100644
index 0000000..5665fd9
--- /dev/null
+++ b/frc971/control_loops/python/drivetrain.py
@@ -0,0 +1,416 @@
+#!/usr/bin/python
+
+from frc971.control_loops.python import control_loop
+from frc971.control_loops.python import controls
+import numpy
+import sys
+from matplotlib import pylab
+import glog
+
+class DrivetrainParams(object):
+ def __init__(self, J, mass, robot_radius, wheel_radius, G_high, G_low,
+ q_pos_low, q_pos_high, q_vel_low, q_vel_high,
+ motor_type = control_loop.CIM(), num_motors = 2, dt = 0.00505,
+ controller_poles=[0.90, 0.90], observer_poles=[0.02, 0.02]):
+ """Defines all constants of a drivetrain.
+
+ Args:
+ J: float, Moment of inertia of drivetrain in kg m^2
+ mass: float, Mass of the robot in kg.
+ robot_radius: float, Radius of the robot, in meters (requires tuning by
+ hand).
+ wheel_radius: float, Radius of the wheels, in meters.
+ G_high: float, Gear ratio for high gear.
+ G_low: float, Gear ratio for low gear.
+ dt: float, Control loop time step.
+ q_pos_low: float, q position low gear.
+ q_pos_high: float, q position high gear.
+ q_vel_low: float, q velocity low gear.
+ q_vel_high: float, q velocity high gear.
+ motor_type: object, class of values defining the motor in drivetrain.
+ num_motors: int, number of motors on one side of drivetrain.
+ controller_poles: array, An array of poles. (See control_loop.py)
+ observer_poles: array, An array of poles. (See control_loop.py)
+ """
+
+ self.J = J
+ self.mass = mass
+ self.robot_radius = robot_radius
+ self.wheel_radius = wheel_radius
+ self.G_high = G_high
+ self.G_low = G_low
+ self.dt = dt
+ self.q_pos_low = q_pos_low
+ self.q_pos_high = q_pos_high
+ self.q_vel_low = q_vel_low
+ self.q_vel_high = q_vel_high
+ self.motor_type = motor_type
+ self.num_motors = num_motors
+ self.controller_poles = controller_poles
+ self.observer_poles = observer_poles
+
+class Drivetrain(control_loop.ControlLoop):
+ def __init__(self, drivetrain_params, name="Drivetrain", left_low=True,
+ right_low=True):
+ """Defines a base drivetrain for a robot.
+
+ Args:
+ drivetrain_params: DrivetrainParams, class of values defining the drivetrain.
+ name: string, Name of this drivetrain.
+ left_low: bool, Whether the left is in high gear.
+ right_low: bool, Whether the right is in high gear.
+ """
+ super(Drivetrain, self).__init__(name)
+
+ # Moment of inertia of the drivetrain in kg m^2
+ self.J = drivetrain_params.J
+ # Mass of the robot, in kg.
+ self.mass = drivetrain_params.mass
+ # Radius of the robot, in meters (requires tuning by hand)
+ self.robot_radius = drivetrain_params.robot_radius
+ # Radius of the wheels, in meters.
+ self.r = drivetrain_params.wheel_radius
+
+ # Gear ratios
+ self.G_low = drivetrain_params.G_low
+ self.G_high = drivetrain_params.G_high
+ if left_low:
+ self.Gl = self.G_low
+ else:
+ self.Gl = self.G_high
+ if right_low:
+ self.Gr = self.G_low
+ else:
+ self.Gr = self.G_high
+
+ # Control loop time step
+ self.dt = drivetrain_params.dt
+
+ self.BuildDrivetrain(drivetrain_params.motor_type, drivetrain_params.num_motors);
+
+ if left_low or right_low:
+ q_pos = drivetrain_params.q_pos_low
+ q_vel = drivetrain_params.q_vel_low
+ else:
+ q_pos = drivetrain_params.q_pos_high
+ q_vel = drivetrain_params.q_vel_high
+
+ self.BuildDrivetrainController(q_pos, q_vel)
+
+ self.InitializeState()
+
+ def BuildDrivetrain(self, motor, num_motors_per_side):
+ self.motor = motor
+ # Number of motors per side
+ self.num_motors = num_motors_per_side
+ # Stall Torque in N m
+ self.stall_torque = motor.stall_torque * self.num_motors * 0.60
+ # Stall Current in Amps
+ self.stall_current = motor.stall_current * self.num_motors
+ # Free Speed in rad/s
+ self.free_speed = motor.free_speed
+ # Free Current in Amps
+ self.free_current = motor.free_current * self.num_motors
+
+ # Effective motor resistance in ohms.
+ self.resistance = 12.0 / self.stall_current
+
+ # Resistance of the motor, divided by the number of motors.
+ # Motor velocity constant
+ self.Kv = (self.free_speed / (12.0 - self.resistance * self.free_current))
+ # Torque constant
+ self.Kt = self.stall_torque / self.stall_current
+
+ # These describe the way that a given side of a robot will be influenced
+ # by the other side. Units of 1 / kg.
+ self.msp = 1.0 / self.mass + self.robot_radius * self.robot_radius / self.J
+ self.msn = 1.0 / self.mass - self.robot_radius * self.robot_radius / self.J
+ # The calculations which we will need for A and B.
+ self.tcl = self.Kt / self.Kv / (self.Gl * self.Gl * self.resistance * self.r * self.r)
+ self.tcr = self.Kt / self.Kv / (self.Gr * self.Gr * self.resistance * self.r * self.r)
+ self.mpl = self.Kt / (self.Gl * self.resistance * self.r)
+ self.mpr = self.Kt / (self.Gr * self.resistance * self.r)
+
+ # State feedback matrices
+ # X will be of the format
+ # [[positionl], [velocityl], [positionr], velocityr]]
+ self.A_continuous = numpy.matrix(
+ [[0, 1, 0, 0],
+ [0, -self.msp * self.tcl, 0, -self.msn * self.tcr],
+ [0, 0, 0, 1],
+ [0, -self.msn * self.tcl, 0, -self.msp * self.tcr]])
+ self.B_continuous = numpy.matrix(
+ [[0, 0],
+ [self.msp * self.mpl, self.msn * self.mpr],
+ [0, 0],
+ [self.msn * self.mpl, self.msp * self.mpr]])
+ self.C = numpy.matrix([[1, 0, 0, 0],
+ [0, 0, 1, 0]])
+ self.D = numpy.matrix([[0, 0],
+ [0, 0]])
+
+ self.A, self.B = self.ContinuousToDiscrete(
+ self.A_continuous, self.B_continuous, self.dt)
+
+ def BuildDrivetrainController(self, q_pos, q_vel):
+ # Tune the LQR controller
+ self.Q = numpy.matrix([[(1.0 / (q_pos ** 2.0)), 0.0, 0.0, 0.0],
+ [0.0, (1.0 / (q_vel ** 2.0)), 0.0, 0.0],
+ [0.0, 0.0, (1.0 / (q_pos ** 2.0)), 0.0],
+ [0.0, 0.0, 0.0, (1.0 / (q_vel ** 2.0))]])
+
+ self.R = numpy.matrix([[(1.0 / (12.0 ** 2.0)), 0.0],
+ [0.0, (1.0 / (12.0 ** 2.0))]])
+ self.K = controls.dlqr(self.A, self.B, self.Q, self.R)
+
+ glog.debug('DT q_pos %f q_vel %s %s', q_pos, q_vel, self._name)
+ glog.debug(str(numpy.linalg.eig(self.A - self.B * self.K)[0]))
+ glog.debug('K %s', repr(self.K))
+
+ self.hlp = 0.3
+ self.llp = 0.4
+ self.PlaceObserverPoles([self.hlp, self.hlp, self.llp, self.llp])
+
+ self.U_max = numpy.matrix([[12.0], [12.0]])
+ self.U_min = numpy.matrix([[-12.0], [-12.0]])
+
+class KFDrivetrain(Drivetrain):
+ def __init__(self, drivetrain_params, name="KFDrivetrain",
+ left_low=True, right_low=True):
+ """Kalman filter values of a drivetrain.
+
+ Args:
+ drivetrain_params: DrivetrainParams, class of values defining the drivetrain.
+ name: string, Name of this drivetrain.
+ left_low: bool, Whether the left is in high gear.
+ right_low: bool, Whether the right is in high gear.
+ """
+ super(KFDrivetrain, self).__init__(drivetrain_params, name, left_low, right_low)
+
+ self.unaugmented_A_continuous = self.A_continuous
+ self.unaugmented_B_continuous = self.B_continuous
+
+ # The practical voltage applied to the wheels is
+ # V_left = U_left + left_voltage_error
+ #
+ # The states are
+ # [left position, left velocity, right position, right velocity,
+ # left voltage error, right voltage error, angular_error]
+ #
+ # The left and right positions are filtered encoder positions and are not
+ # adjusted for heading error.
+ # The turn velocity as computed by the left and right velocities is
+ # adjusted by the gyro velocity.
+ # The angular_error is the angular velocity error between the wheel speed
+ # and the gyro speed.
+ self.A_continuous = numpy.matrix(numpy.zeros((7, 7)))
+ self.B_continuous = numpy.matrix(numpy.zeros((7, 2)))
+ self.A_continuous[0:4,0:4] = self.unaugmented_A_continuous
+ self.A_continuous[0:4,4:6] = self.unaugmented_B_continuous
+ self.B_continuous[0:4,0:2] = self.unaugmented_B_continuous
+ self.A_continuous[0,6] = 1
+ self.A_continuous[2,6] = -1
+
+ self.A, self.B = self.ContinuousToDiscrete(
+ self.A_continuous, self.B_continuous, self.dt)
+
+ self.C = numpy.matrix([[1, 0, 0, 0, 0, 0, 0],
+ [0, 0, 1, 0, 0, 0, 0],
+ [0, -0.5 / drivetrain_params.robot_radius, 0, 0.5 / drivetrain_params.robot_radius, 0, 0, 0]])
+
+ self.D = numpy.matrix([[0, 0],
+ [0, 0],
+ [0, 0]])
+
+ q_pos = 0.05
+ q_vel = 1.00
+ q_voltage = 10.0
+ q_encoder_uncertainty = 2.00
+
+ self.Q = numpy.matrix([[(q_pos ** 2.0), 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, (q_vel ** 2.0), 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, (q_pos ** 2.0), 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, (q_vel ** 2.0), 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, (q_voltage ** 2.0), 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, (q_voltage ** 2.0), 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, (q_encoder_uncertainty ** 2.0)]])
+
+ r_pos = 0.0001
+ r_gyro = 0.000001
+ self.R = numpy.matrix([[(r_pos ** 2.0), 0.0, 0.0],
+ [0.0, (r_pos ** 2.0), 0.0],
+ [0.0, 0.0, (r_gyro ** 2.0)]])
+
+ # Solving for kf gains.
+ self.KalmanGain, self.Q_steady = controls.kalman(
+ A=self.A, B=self.B, C=self.C, Q=self.Q, R=self.R)
+
+ self.L = self.A * self.KalmanGain
+
+ unaug_K = self.K
+
+ # Implement a nice closed loop controller for use by the closed loop
+ # controller.
+ self.K = numpy.matrix(numpy.zeros((self.B.shape[1], self.A.shape[0])))
+ self.K[0:2, 0:4] = unaug_K
+ self.K[0, 4] = 1.0
+ self.K[1, 5] = 1.0
+
+ self.Qff = numpy.matrix(numpy.zeros((4, 4)))
+ qff_pos = 0.005
+ qff_vel = 1.00
+ self.Qff[0, 0] = 1.0 / qff_pos ** 2.0
+ self.Qff[1, 1] = 1.0 / qff_vel ** 2.0
+ self.Qff[2, 2] = 1.0 / qff_pos ** 2.0
+ self.Qff[3, 3] = 1.0 / qff_vel ** 2.0
+ self.Kff = numpy.matrix(numpy.zeros((2, 7)))
+ self.Kff[0:2, 0:4] = controls.TwoStateFeedForwards(self.B[0:4,:], self.Qff)
+
+ self.InitializeState()
+
+
+def WriteDrivetrain(drivetrain_files, kf_drivetrain_files, year_namespace,
+ drivetrain_params):
+
+ # Write the generated constants out to a file.
+ drivetrain_low_low = Drivetrain(name="DrivetrainLowLow",
+ left_low=True, right_low=True, drivetrain_params=drivetrain_params)
+ drivetrain_low_high = Drivetrain(name="DrivetrainLowHigh",
+ left_low=True, right_low=False, drivetrain_params=drivetrain_params)
+ drivetrain_high_low = Drivetrain(name="DrivetrainHighLow",
+ left_low=False, right_low=True, drivetrain_params=drivetrain_params)
+ drivetrain_high_high = Drivetrain(name="DrivetrainHighHigh",
+ left_low=False, right_low=False, drivetrain_params=drivetrain_params)
+
+ kf_drivetrain_low_low = KFDrivetrain(name="KFDrivetrainLowLow",
+ left_low=True, right_low=True, drivetrain_params=drivetrain_params)
+ kf_drivetrain_low_high = KFDrivetrain(name="KFDrivetrainLowHigh",
+ left_low=True, right_low=False, drivetrain_params=drivetrain_params)
+ kf_drivetrain_high_low = KFDrivetrain(name="KFDrivetrainHighLow",
+ left_low=False, right_low=True, drivetrain_params=drivetrain_params)
+ kf_drivetrain_high_high = KFDrivetrain(name="KFDrivetrainHighHigh",
+ left_low=False, right_low=False, drivetrain_params=drivetrain_params)
+
+ namespaces = [year_namespace, 'control_loops', 'drivetrain']
+ dog_loop_writer = control_loop.ControlLoopWriter(
+ "Drivetrain", [drivetrain_low_low, drivetrain_low_high,
+ drivetrain_high_low, drivetrain_high_high],
+ namespaces = namespaces)
+ dog_loop_writer.AddConstant(control_loop.Constant("kDt", "%f",
+ drivetrain_low_low.dt))
+ dog_loop_writer.AddConstant(control_loop.Constant("kStallTorque", "%f",
+ drivetrain_low_low.stall_torque))
+ dog_loop_writer.AddConstant(control_loop.Constant("kStallCurrent", "%f",
+ drivetrain_low_low.stall_current))
+ dog_loop_writer.AddConstant(control_loop.Constant("kFreeSpeed", "%f",
+ drivetrain_low_low.free_speed))
+ dog_loop_writer.AddConstant(control_loop.Constant("kFreeCurrent", "%f",
+ drivetrain_low_low.free_current))
+ dog_loop_writer.AddConstant(control_loop.Constant("kJ", "%f",
+ drivetrain_low_low.J))
+ dog_loop_writer.AddConstant(control_loop.Constant("kMass", "%f",
+ drivetrain_low_low.mass))
+ dog_loop_writer.AddConstant(control_loop.Constant("kRobotRadius", "%f",
+ drivetrain_low_low.robot_radius))
+ dog_loop_writer.AddConstant(control_loop.Constant("kWheelRadius", "%f",
+ drivetrain_low_low.r))
+ dog_loop_writer.AddConstant(control_loop.Constant("kR", "%f",
+ drivetrain_low_low.resistance))
+ dog_loop_writer.AddConstant(control_loop.Constant("kV", "%f",
+ drivetrain_low_low.Kv))
+ dog_loop_writer.AddConstant(control_loop.Constant("kT", "%f",
+ drivetrain_low_low.Kt))
+ dog_loop_writer.AddConstant(control_loop.Constant("kLowGearRatio", "%f",
+ drivetrain_low_low.G_low))
+ dog_loop_writer.AddConstant(control_loop.Constant("kHighGearRatio", "%f",
+ drivetrain_high_high.G_high))
+ dog_loop_writer.AddConstant(control_loop.Constant("kHighOutputRatio", "%f",
+ drivetrain_high_high.G_high * drivetrain_high_high.r))
+
+ dog_loop_writer.Write(drivetrain_files[0], drivetrain_files[1])
+
+ kf_loop_writer = control_loop.ControlLoopWriter(
+ "KFDrivetrain", [kf_drivetrain_low_low, kf_drivetrain_low_high,
+ kf_drivetrain_high_low, kf_drivetrain_high_high],
+ namespaces = namespaces)
+ kf_loop_writer.Write(kf_drivetrain_files[0], kf_drivetrain_files[1])
+
+def PlotDrivetrainMotions(drivetrain_params):
+ # Simulate the response of the system to a step input.
+ drivetrain = Drivetrain(left_low=False, right_low=False, drivetrain_params=drivetrain_params)
+ simulated_left = []
+ simulated_right = []
+ for _ in xrange(100):
+ drivetrain.Update(numpy.matrix([[12.0], [12.0]]))
+ simulated_left.append(drivetrain.X[0, 0])
+ simulated_right.append(drivetrain.X[2, 0])
+
+ pylab.rc('lines', linewidth=4)
+ pylab.plot(range(100), simulated_left, label='left position')
+ pylab.plot(range(100), simulated_right, 'r--', label='right position')
+ pylab.suptitle('Acceleration Test\n12 Volt Step Input')
+ pylab.legend(loc='lower right')
+ pylab.show()
+
+ # Simulate forwards motion.
+ drivetrain = Drivetrain(left_low=False, right_low=False, drivetrain_params=drivetrain_params)
+ close_loop_left = []
+ close_loop_right = []
+ left_power = []
+ right_power = []
+ R = numpy.matrix([[1.0], [0.0], [1.0], [0.0]])
+ for _ in xrange(300):
+ U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
+ drivetrain.U_min, drivetrain.U_max)
+ drivetrain.UpdateObserver(U)
+ drivetrain.Update(U)
+ close_loop_left.append(drivetrain.X[0, 0])
+ close_loop_right.append(drivetrain.X[2, 0])
+ left_power.append(U[0, 0])
+ right_power.append(U[1, 0])
+
+ pylab.plot(range(300), close_loop_left, label='left position')
+ pylab.plot(range(300), close_loop_right, 'm--', label='right position')
+ pylab.plot(range(300), left_power, label='left power')
+ pylab.plot(range(300), right_power, '--', label='right power')
+ pylab.suptitle('Linear Move\nLeft and Right Position going to 1')
+ pylab.legend()
+ pylab.show()
+
+ # Try turning in place
+ drivetrain = Drivetrain(drivetrain_params=drivetrain_params)
+ close_loop_left = []
+ close_loop_right = []
+ R = numpy.matrix([[-1.0], [0.0], [1.0], [0.0]])
+ for _ in xrange(200):
+ U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
+ drivetrain.U_min, drivetrain.U_max)
+ drivetrain.UpdateObserver(U)
+ drivetrain.Update(U)
+ close_loop_left.append(drivetrain.X[0, 0])
+ close_loop_right.append(drivetrain.X[2, 0])
+
+ pylab.plot(range(200), close_loop_left, label='left position')
+ pylab.plot(range(200), close_loop_right, label='right position')
+ pylab.suptitle('Angular Move\nLeft position going to -1 and right position going to 1')
+ pylab.legend(loc='center right')
+ pylab.show()
+
+ # Try turning just one side.
+ drivetrain = Drivetrain(drivetrain_params=drivetrain_params)
+ close_loop_left = []
+ close_loop_right = []
+ R = numpy.matrix([[0.0], [0.0], [1.0], [0.0]])
+ for _ in xrange(300):
+ U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
+ drivetrain.U_min, drivetrain.U_max)
+ drivetrain.UpdateObserver(U)
+ drivetrain.Update(U)
+ close_loop_left.append(drivetrain.X[0, 0])
+ close_loop_right.append(drivetrain.X[2, 0])
+
+ pylab.plot(range(300), close_loop_left, label='left position')
+ pylab.plot(range(300), close_loop_right, label='right position')
+ pylab.suptitle('Pivot\nLeft position not changing and right position going to 1')
+ pylab.legend(loc='center right')
+ pylab.show()
diff --git a/frc971/control_loops/python/polydrivetrain.py b/frc971/control_loops/python/polydrivetrain.py
new file mode 100644
index 0000000..c9c9efe
--- /dev/null
+++ b/frc971/control_loops/python/polydrivetrain.py
@@ -0,0 +1,488 @@
+#!/usr/bin/python
+
+import numpy
+from frc971.control_loops.python import polytope
+import frc971.control_loops.python.drivetrain
+from frc971.control_loops.python import control_loop
+from frc971.control_loops.python import controls
+from frc971.control_loops.python.cim import CIM
+from matplotlib import pylab
+
+import glog
+
+def CoerceGoal(region, K, w, R):
+ """Intersects a line with a region, and finds the closest point to R.
+
+ Finds a point that is closest to R inside the region, and on the line
+ defined by K X = w. If it is not possible to find a point on the line,
+ finds a point that is inside the region and closest to the line. This
+ function assumes that
+
+ Args:
+ region: HPolytope, the valid goal region.
+ K: numpy.matrix (2 x 1), the matrix for the equation [K1, K2] [x1; x2] = w
+ w: float, the offset in the equation above.
+ R: numpy.matrix (2 x 1), the point to be closest to.
+
+ Returns:
+ numpy.matrix (2 x 1), the point.
+ """
+ return DoCoerceGoal(region, K, w, R)[0]
+
+def DoCoerceGoal(region, K, w, R):
+ if region.IsInside(R):
+ return (R, True)
+
+ perpendicular_vector = K.T / numpy.linalg.norm(K)
+ parallel_vector = numpy.matrix([[perpendicular_vector[1, 0]],
+ [-perpendicular_vector[0, 0]]])
+
+ # We want to impose the constraint K * X = w on the polytope H * X <= k.
+ # We do this by breaking X up into parallel and perpendicular components to
+ # the half plane. This gives us the following equation.
+ #
+ # parallel * (parallel.T \dot X) + perpendicular * (perpendicular \dot X)) = X
+ #
+ # Then, substitute this into the polytope.
+ #
+ # H * (parallel * (parallel.T \dot X) + perpendicular * (perpendicular \dot X)) <= k
+ #
+ # Substitute K * X = w
+ #
+ # H * parallel * (parallel.T \dot X) + H * perpendicular * w <= k
+ #
+ # Move all the knowns to the right side.
+ #
+ # H * parallel * ([parallel1 parallel2] * X) <= k - H * perpendicular * w
+ #
+ # Let t = parallel.T \dot X, the component parallel to the surface.
+ #
+ # H * parallel * t <= k - H * perpendicular * w
+ #
+ # This is a polytope which we can solve, and use to figure out the range of X
+ # that we care about!
+
+ t_poly = polytope.HPolytope(
+ region.H * parallel_vector,
+ region.k - region.H * perpendicular_vector * w)
+
+ vertices = t_poly.Vertices()
+
+ if vertices.shape[0]:
+ # The region exists!
+ # Find the closest vertex
+ min_distance = numpy.infty
+ closest_point = None
+ for vertex in vertices:
+ point = parallel_vector * vertex + perpendicular_vector * w
+ length = numpy.linalg.norm(R - point)
+ if length < min_distance:
+ min_distance = length
+ closest_point = point
+
+ return (closest_point, True)
+ else:
+ # Find the vertex of the space that is closest to the line.
+ region_vertices = region.Vertices()
+ min_distance = numpy.infty
+ closest_point = None
+ for vertex in region_vertices:
+ point = vertex.T
+ length = numpy.abs((perpendicular_vector.T * point)[0, 0])
+ if length < min_distance:
+ min_distance = length
+ closest_point = point
+
+ return (closest_point, False)
+
+class VelocityDrivetrainModel(control_loop.ControlLoop):
+ def __init__(self, drivetrain_params, left_low=True, right_low=True,
+ name="VelocityDrivetrainModel"):
+ super(VelocityDrivetrainModel, self).__init__(name)
+ self._drivetrain = frc971.control_loops.python.drivetrain.Drivetrain(
+ left_low=left_low, right_low=right_low,
+ drivetrain_params=drivetrain_params)
+ self.dt = drivetrain_params.dt
+ self.A_continuous = numpy.matrix(
+ [[self._drivetrain.A_continuous[1, 1], self._drivetrain.A_continuous[1, 3]],
+ [self._drivetrain.A_continuous[3, 1], self._drivetrain.A_continuous[3, 3]]])
+
+ self.B_continuous = numpy.matrix(
+ [[self._drivetrain.B_continuous[1, 0], self._drivetrain.B_continuous[1, 1]],
+ [self._drivetrain.B_continuous[3, 0], self._drivetrain.B_continuous[3, 1]]])
+ self.C = numpy.matrix(numpy.eye(2))
+ self.D = numpy.matrix(numpy.zeros((2, 2)))
+
+ self.A, self.B = self.ContinuousToDiscrete(self.A_continuous,
+ self.B_continuous, self.dt)
+
+ # FF * X = U (steady state)
+ self.FF = self.B.I * (numpy.eye(2) - self.A)
+
+ self.PlaceControllerPoles(drivetrain_params.controller_poles)
+ self.PlaceObserverPoles(drivetrain_params.observer_poles)
+
+ self.G_high = self._drivetrain.G_high
+ self.G_low = self._drivetrain.G_low
+ self.resistance = self._drivetrain.resistance
+ self.r = self._drivetrain.r
+ self.Kv = self._drivetrain.Kv
+ self.Kt = self._drivetrain.Kt
+
+ self.U_max = self._drivetrain.U_max
+ self.U_min = self._drivetrain.U_min
+
+
+class VelocityDrivetrain(object):
+ HIGH = 'high'
+ LOW = 'low'
+ SHIFTING_UP = 'up'
+ SHIFTING_DOWN = 'down'
+
+ def __init__(self, drivetrain_params):
+ self.drivetrain_low_low = VelocityDrivetrainModel(
+ left_low=True, right_low=True, name='VelocityDrivetrainLowLow',
+ drivetrain_params=drivetrain_params)
+ self.drivetrain_low_high = VelocityDrivetrainModel(
+ left_low=True, right_low=False, name='VelocityDrivetrainLowHigh',
+ drivetrain_params=drivetrain_params)
+ self.drivetrain_high_low = VelocityDrivetrainModel(
+ left_low=False, right_low=True, name = 'VelocityDrivetrainHighLow',
+ drivetrain_params=drivetrain_params)
+ self.drivetrain_high_high = VelocityDrivetrainModel(
+ left_low=False, right_low=False, name = 'VelocityDrivetrainHighHigh',
+ drivetrain_params=drivetrain_params)
+
+ # X is [lvel, rvel]
+ self.X = numpy.matrix(
+ [[0.0],
+ [0.0]])
+
+ self.U_poly = polytope.HPolytope(
+ numpy.matrix([[1, 0],
+ [-1, 0],
+ [0, 1],
+ [0, -1]]),
+ numpy.matrix([[12],
+ [12],
+ [12],
+ [12]]))
+
+ self.U_max = numpy.matrix(
+ [[12.0],
+ [12.0]])
+ self.U_min = numpy.matrix(
+ [[-12.0000000000],
+ [-12.0000000000]])
+
+ self.dt = 0.00505
+
+ self.R = numpy.matrix(
+ [[0.0],
+ [0.0]])
+
+ self.U_ideal = numpy.matrix(
+ [[0.0],
+ [0.0]])
+
+ # ttrust is the comprimise between having full throttle negative inertia,
+ # and having no throttle negative inertia. A value of 0 is full throttle
+ # inertia. A value of 1 is no throttle negative inertia.
+ self.ttrust = 1.0
+
+ self.left_gear = VelocityDrivetrain.LOW
+ self.right_gear = VelocityDrivetrain.LOW
+ self.left_shifter_position = 0.0
+ self.right_shifter_position = 0.0
+ self.left_cim = CIM()
+ self.right_cim = CIM()
+
+ def IsInGear(self, gear):
+ return gear is VelocityDrivetrain.HIGH or gear is VelocityDrivetrain.LOW
+
+ def MotorRPM(self, shifter_position, velocity):
+ if shifter_position > 0.5:
+ return (velocity / self.CurrentDrivetrain().G_high /
+ self.CurrentDrivetrain().r)
+ else:
+ return (velocity / self.CurrentDrivetrain().G_low /
+ self.CurrentDrivetrain().r)
+
+ def CurrentDrivetrain(self):
+ if self.left_shifter_position > 0.5:
+ if self.right_shifter_position > 0.5:
+ return self.drivetrain_high_high
+ else:
+ return self.drivetrain_high_low
+ else:
+ if self.right_shifter_position > 0.5:
+ return self.drivetrain_low_high
+ else:
+ return self.drivetrain_low_low
+
+ def SimShifter(self, gear, shifter_position):
+ if gear is VelocityDrivetrain.HIGH or gear is VelocityDrivetrain.SHIFTING_UP:
+ shifter_position = min(shifter_position + 0.5, 1.0)
+ else:
+ shifter_position = max(shifter_position - 0.5, 0.0)
+
+ if shifter_position == 1.0:
+ gear = VelocityDrivetrain.HIGH
+ elif shifter_position == 0.0:
+ gear = VelocityDrivetrain.LOW
+
+ return gear, shifter_position
+
+ def ComputeGear(self, wheel_velocity, should_print=False, current_gear=False, gear_name=None):
+ high_omega = (wheel_velocity / self.CurrentDrivetrain().G_high /
+ self.CurrentDrivetrain().r)
+ low_omega = (wheel_velocity / self.CurrentDrivetrain().G_low /
+ self.CurrentDrivetrain().r)
+ #print gear_name, "Motor Energy Difference.", 0.5 * 0.000140032647 * (low_omega * low_omega - high_omega * high_omega), "joules"
+ high_torque = ((12.0 - high_omega / self.CurrentDrivetrain().Kv) *
+ self.CurrentDrivetrain().Kt / self.CurrentDrivetrain().resistance)
+ low_torque = ((12.0 - low_omega / self.CurrentDrivetrain().Kv) *
+ self.CurrentDrivetrain().Kt / self.CurrentDrivetrain().resistance)
+ high_power = high_torque * high_omega
+ low_power = low_torque * low_omega
+ #if should_print:
+ # print gear_name, "High omega", high_omega, "Low omega", low_omega
+ # print gear_name, "High torque", high_torque, "Low torque", low_torque
+ # print gear_name, "High power", high_power, "Low power", low_power
+
+ # Shift algorithm improvements.
+ # TODO(aschuh):
+ # It takes time to shift. Shifting down for 1 cycle doesn't make sense
+ # because you will end up slower than without shifting. Figure out how
+ # to include that info.
+ # If the driver is still in high gear, but isn't asking for the extra power
+ # from low gear, don't shift until he asks for it.
+ goal_gear_is_high = high_power > low_power
+ #goal_gear_is_high = True
+
+ if not self.IsInGear(current_gear):
+ glog.debug('%s Not in gear.', gear_name)
+ return current_gear
+ else:
+ is_high = current_gear is VelocityDrivetrain.HIGH
+ if is_high != goal_gear_is_high:
+ if goal_gear_is_high:
+ glog.debug('%s Shifting up.', gear_name)
+ return VelocityDrivetrain.SHIFTING_UP
+ else:
+ glog.debug('%s Shifting down.', gear_name)
+ return VelocityDrivetrain.SHIFTING_DOWN
+ else:
+ return current_gear
+
+ def FilterVelocity(self, throttle):
+ # Invert the plant to figure out how the velocity filter would have to work
+ # out in order to filter out the forwards negative inertia.
+ # This math assumes that the left and right power and velocity are equal.
+
+ # The throttle filter should filter such that the motor in the highest gear
+ # should be controlling the time constant.
+ # Do this by finding the index of FF that has the lowest value, and computing
+ # the sums using that index.
+ FF_sum = self.CurrentDrivetrain().FF.sum(axis=1)
+ min_FF_sum_index = numpy.argmin(FF_sum)
+ min_FF_sum = FF_sum[min_FF_sum_index, 0]
+ min_K_sum = self.CurrentDrivetrain().K[min_FF_sum_index, :].sum()
+ # Compute the FF sum for high gear.
+ high_min_FF_sum = self.drivetrain_high_high.FF[0, :].sum()
+
+ # U = self.K[0, :].sum() * (R - x_avg) + self.FF[0, :].sum() * R
+ # throttle * 12.0 = (self.K[0, :].sum() + self.FF[0, :].sum()) * R
+ # - self.K[0, :].sum() * x_avg
+
+ # R = (throttle * 12.0 + self.K[0, :].sum() * x_avg) /
+ # (self.K[0, :].sum() + self.FF[0, :].sum())
+
+ # U = (K + FF) * R - K * X
+ # (K + FF) ^-1 * (U + K * X) = R
+
+ # Scale throttle by min_FF_sum / high_min_FF_sum. This will make low gear
+ # have the same velocity goal as high gear, and so that the robot will hold
+ # the same speed for the same throttle for all gears.
+ adjusted_ff_voltage = numpy.clip(throttle * 12.0 * min_FF_sum / high_min_FF_sum, -12.0, 12.0)
+ return ((adjusted_ff_voltage + self.ttrust * min_K_sum * (self.X[0, 0] + self.X[1, 0]) / 2.0)
+ / (self.ttrust * min_K_sum + min_FF_sum))
+
+ def Update(self, throttle, steering):
+ # Shift into the gear which sends the most power to the floor.
+ # This is the same as sending the most torque down to the floor at the
+ # wheel.
+
+ self.left_gear = self.right_gear = True
+ if True:
+ self.left_gear = self.ComputeGear(self.X[0, 0], should_print=True,
+ current_gear=self.left_gear,
+ gear_name="left")
+ self.right_gear = self.ComputeGear(self.X[1, 0], should_print=True,
+ current_gear=self.right_gear,
+ gear_name="right")
+ if self.IsInGear(self.left_gear):
+ self.left_cim.X[0, 0] = self.MotorRPM(self.left_shifter_position, self.X[0, 0])
+
+ if self.IsInGear(self.right_gear):
+ self.right_cim.X[0, 0] = self.MotorRPM(self.right_shifter_position, self.X[0, 0])
+
+ if self.IsInGear(self.left_gear) and self.IsInGear(self.right_gear):
+ # Filter the throttle to provide a nicer response.
+ fvel = self.FilterVelocity(throttle)
+
+ # Constant radius means that angualar_velocity / linear_velocity = constant.
+ # Compute the left and right velocities.
+ steering_velocity = numpy.abs(fvel) * steering
+ left_velocity = fvel - steering_velocity
+ right_velocity = fvel + steering_velocity
+
+ # Write this constraint in the form of K * R = w
+ # angular velocity / linear velocity = constant
+ # (left - right) / (left + right) = constant
+ # left - right = constant * left + constant * right
+
+ # (fvel - steering * numpy.abs(fvel) - fvel - steering * numpy.abs(fvel)) /
+ # (fvel - steering * numpy.abs(fvel) + fvel + steering * numpy.abs(fvel)) =
+ # constant
+ # (- 2 * steering * numpy.abs(fvel)) / (2 * fvel) = constant
+ # (-steering * sign(fvel)) = constant
+ # (-steering * sign(fvel)) * (left + right) = left - right
+ # (steering * sign(fvel) + 1) * left + (steering * sign(fvel) - 1) * right = 0
+
+ equality_k = numpy.matrix(
+ [[1 + steering * numpy.sign(fvel), -(1 - steering * numpy.sign(fvel))]])
+ equality_w = 0.0
+
+ self.R[0, 0] = left_velocity
+ self.R[1, 0] = right_velocity
+
+ # Construct a constraint on R by manipulating the constraint on U
+ # Start out with H * U <= k
+ # U = FF * R + K * (R - X)
+ # H * (FF * R + K * R - K * X) <= k
+ # H * (FF + K) * R <= k + H * K * X
+ R_poly = polytope.HPolytope(
+ self.U_poly.H * (self.CurrentDrivetrain().K + self.CurrentDrivetrain().FF),
+ self.U_poly.k + self.U_poly.H * self.CurrentDrivetrain().K * self.X)
+
+ # Limit R back inside the box.
+ self.boxed_R = CoerceGoal(R_poly, equality_k, equality_w, self.R)
+
+ FF_volts = self.CurrentDrivetrain().FF * self.boxed_R
+ self.U_ideal = self.CurrentDrivetrain().K * (self.boxed_R - self.X) + FF_volts
+ else:
+ glog.debug('Not all in gear')
+ if not self.IsInGear(self.left_gear) and not self.IsInGear(self.right_gear):
+ # TODO(austin): Use battery volts here.
+ R_left = self.MotorRPM(self.left_shifter_position, self.X[0, 0])
+ self.U_ideal[0, 0] = numpy.clip(
+ self.left_cim.K * (R_left - self.left_cim.X) + R_left / self.left_cim.Kv,
+ self.left_cim.U_min, self.left_cim.U_max)
+ self.left_cim.Update(self.U_ideal[0, 0])
+
+ R_right = self.MotorRPM(self.right_shifter_position, self.X[1, 0])
+ self.U_ideal[1, 0] = numpy.clip(
+ self.right_cim.K * (R_right - self.right_cim.X) + R_right / self.right_cim.Kv,
+ self.right_cim.U_min, self.right_cim.U_max)
+ self.right_cim.Update(self.U_ideal[1, 0])
+ else:
+ assert False
+
+ self.U = numpy.clip(self.U_ideal, self.U_min, self.U_max)
+
+ # TODO(austin): Model the robot as not accelerating when you shift...
+ # This hack only works when you shift at the same time.
+ if self.IsInGear(self.left_gear) and self.IsInGear(self.right_gear):
+ self.X = self.CurrentDrivetrain().A * self.X + self.CurrentDrivetrain().B * self.U
+
+ self.left_gear, self.left_shifter_position = self.SimShifter(
+ self.left_gear, self.left_shifter_position)
+ self.right_gear, self.right_shifter_position = self.SimShifter(
+ self.right_gear, self.right_shifter_position)
+
+ glog.debug('U is %s %s', str(self.U[0, 0]), str(self.U[1, 0]))
+ glog.debug('Left shifter %s %d Right shifter %s %d',
+ self.left_gear, self.left_shifter_position,
+ self.right_gear, self.right_shifter_position)
+
+def WritePolyDrivetrain(drivetrain_files, motor_files, year_namespace,
+ drivetrain_params):
+ vdrivetrain = VelocityDrivetrain(drivetrain_params)
+ namespaces = [year_namespace, 'control_loops', 'drivetrain']
+ dog_loop_writer = control_loop.ControlLoopWriter(
+ "VelocityDrivetrain", [vdrivetrain.drivetrain_low_low,
+ vdrivetrain.drivetrain_low_high,
+ vdrivetrain.drivetrain_high_low,
+ vdrivetrain.drivetrain_high_high],
+ namespaces=namespaces)
+
+ dog_loop_writer.Write(drivetrain_files[0], drivetrain_files[1])
+
+ cim_writer = control_loop.ControlLoopWriter("CIM", [CIM()])
+
+ cim_writer.Write(motor_files[0], motor_files[1])
+
+def PlotPolyDrivetrainMotions(drivetrain_params):
+ vdrivetrain = VelocityDrivetrain(drivetrain_params)
+ vl_plot = []
+ vr_plot = []
+ ul_plot = []
+ ur_plot = []
+ radius_plot = []
+ t_plot = []
+ left_gear_plot = []
+ right_gear_plot = []
+ vdrivetrain.left_shifter_position = 0.0
+ vdrivetrain.right_shifter_position = 0.0
+ vdrivetrain.left_gear = VelocityDrivetrain.LOW
+ vdrivetrain.right_gear = VelocityDrivetrain.LOW
+
+ glog.debug('K is %s', str(vdrivetrain.CurrentDrivetrain().K))
+
+ if vdrivetrain.left_gear is VelocityDrivetrain.HIGH:
+ glog.debug('Left is high')
+ else:
+ glog.debug('Left is low')
+ if vdrivetrain.right_gear is VelocityDrivetrain.HIGH:
+ glog.debug('Right is high')
+ else:
+ glog.debug('Right is low')
+
+ for t in numpy.arange(0, 1.7, vdrivetrain.dt):
+ if t < 0.5:
+ vdrivetrain.Update(throttle=0.00, steering=1.0)
+ elif t < 1.2:
+ vdrivetrain.Update(throttle=0.5, steering=1.0)
+ else:
+ vdrivetrain.Update(throttle=0.00, steering=1.0)
+ t_plot.append(t)
+ vl_plot.append(vdrivetrain.X[0, 0])
+ vr_plot.append(vdrivetrain.X[1, 0])
+ ul_plot.append(vdrivetrain.U[0, 0])
+ ur_plot.append(vdrivetrain.U[1, 0])
+ left_gear_plot.append((vdrivetrain.left_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
+ right_gear_plot.append((vdrivetrain.right_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
+
+ fwd_velocity = (vdrivetrain.X[1, 0] + vdrivetrain.X[0, 0]) / 2
+ turn_velocity = (vdrivetrain.X[1, 0] - vdrivetrain.X[0, 0])
+ if abs(fwd_velocity) < 0.0000001:
+ radius_plot.append(turn_velocity)
+ else:
+ radius_plot.append(turn_velocity / fwd_velocity)
+
+ # TODO(austin):
+ # Shifting compensation.
+
+ # Tighten the turn.
+ # Closed loop drive.
+
+ pylab.plot(t_plot, vl_plot, label='left velocity')
+ pylab.plot(t_plot, vr_plot, label='right velocity')
+ pylab.plot(t_plot, ul_plot, label='left voltage')
+ pylab.plot(t_plot, ur_plot, label='right voltage')
+ pylab.plot(t_plot, radius_plot, label='radius')
+ pylab.plot(t_plot, left_gear_plot, label='left gear high')
+ pylab.plot(t_plot, right_gear_plot, label='right gear high')
+ pylab.legend()
+ pylab.show()
diff --git a/y2017/control_loops/python/BUILD b/y2017/control_loops/python/BUILD
index 7365124..83473ae 100644
--- a/y2017/control_loops/python/BUILD
+++ b/y2017/control_loops/python/BUILD
@@ -8,7 +8,7 @@
deps = [
'//external:python-gflags',
'//external:python-glog',
- '//frc971/control_loops/python:controls',
+ '//frc971/control_loops/python:drivetrain',
],
restricted_to = ['//tools:k8'],
)
@@ -22,7 +22,7 @@
deps = [
'//external:python-gflags',
'//external:python-glog',
- '//frc971/control_loops/python:controls',
+ '//frc971/control_loops/python:polydrivetrain',
],
restricted_to = ['//tools:k8'],
)
@@ -37,6 +37,7 @@
'//external:python-gflags',
'//external:python-glog',
'//frc971/control_loops/python:controls',
+ '//frc971/control_loops/python:drivetrain',
],
restricted_to = ['//tools:k8'],
)
diff --git a/y2017/control_loops/python/drivetrain.py b/y2017/control_loops/python/drivetrain.py
index 541d158..b4635ee 100755
--- a/y2017/control_loops/python/drivetrain.py
+++ b/y2017/control_loops/python/drivetrain.py
@@ -1,10 +1,7 @@
#!/usr/bin/python
-from frc971.control_loops.python import control_loop
-from frc971.control_loops.python import controls
-import numpy
+from frc971.control_loops.python import drivetrain
import sys
-from matplotlib import pylab
import gflags
import glog
@@ -13,351 +10,28 @@
gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.')
-
-class Drivetrain(control_loop.ControlLoop):
- def __init__(self, name="Drivetrain", left_low=True, right_low=True):
- super(Drivetrain, self).__init__(name)
- # Number of motors per side
- self.num_motors = 2
- # Stall Torque in N m
- self.stall_torque = 2.42 * self.num_motors * 0.60
- # Stall Current in Amps
- self.stall_current = 133.0 * self.num_motors
- self.free_speed_rpm = 5500.0
- # Free Speed in rotations/second.
- self.free_speed = self.free_speed_rpm / 60
- # Free Current in Amps
- self.free_current = 4.7 * self.num_motors
- # Moment of inertia of the drivetrain in kg m^2
- self.J = 6.0
- # Mass of the robot, in kg.
- self.m = 52
- # Radius of the robot, in meters (requires tuning by hand)
- self.rb = 0.59055 / 2.0
- # Radius of the wheels, in meters.
- self.r = 0.08255 / 2.0
- # Resistance of the motor, divided by the number of motors.
- self.resistance = 12.0 / self.stall_current
- # Motor velocity constant
- self.Kv = ((self.free_speed * 2.0 * numpy.pi) /
- (12.0 - self.resistance * self.free_current))
- # Torque constant
- self.Kt = self.stall_torque / self.stall_current
- # Gear ratios
- self.G_low = 11.0 / 60.0
- self.G_high = 11.0 / 60.0
- if left_low:
- self.Gl = self.G_low
- else:
- self.Gl = self.G_high
- if right_low:
- self.Gr = self.G_low
- else:
- self.Gr = self.G_high
-
- # Control loop time step
- self.dt = 0.00505
-
- # These describe the way that a given side of a robot will be influenced
- # by the other side. Units of 1 / kg.
- self.msp = 1.0 / self.m + self.rb * self.rb / self.J
- self.msn = 1.0 / self.m - self.rb * self.rb / self.J
- # The calculations which we will need for A and B.
- self.tcl = -self.Kt / self.Kv / (self.Gl * self.Gl * self.resistance * self.r * self.r)
- self.tcr = -self.Kt / self.Kv / (self.Gr * self.Gr * self.resistance * self.r * self.r)
- self.mpl = self.Kt / (self.Gl * self.resistance * self.r)
- self.mpr = self.Kt / (self.Gr * self.resistance * self.r)
-
- # State feedback matrices
- # X will be of the format
- # [[positionl], [velocityl], [positionr], velocityr]]
- self.A_continuous = numpy.matrix(
- [[0, 1, 0, 0],
- [0, self.msp * self.tcl, 0, self.msn * self.tcr],
- [0, 0, 0, 1],
- [0, self.msn * self.tcl, 0, self.msp * self.tcr]])
- self.B_continuous = numpy.matrix(
- [[0, 0],
- [self.msp * self.mpl, self.msn * self.mpr],
- [0, 0],
- [self.msn * self.mpl, self.msp * self.mpr]])
- self.C = numpy.matrix([[1, 0, 0, 0],
- [0, 0, 1, 0]])
- self.D = numpy.matrix([[0, 0],
- [0, 0]])
-
- self.A, self.B = self.ContinuousToDiscrete(
- self.A_continuous, self.B_continuous, self.dt)
-
- if left_low or right_low:
- q_pos = 0.12
- q_vel = 1.0
- else:
- q_pos = 0.14
- q_vel = 0.95
-
- # Tune the LQR controller
- self.Q = numpy.matrix([[(1.0 / (q_pos ** 2.0)), 0.0, 0.0, 0.0],
- [0.0, (1.0 / (q_vel ** 2.0)), 0.0, 0.0],
- [0.0, 0.0, (1.0 / (q_pos ** 2.0)), 0.0],
- [0.0, 0.0, 0.0, (1.0 / (q_vel ** 2.0))]])
-
- self.R = numpy.matrix([[(1.0 / (12.0 ** 2.0)), 0.0],
- [0.0, (1.0 / (12.0 ** 2.0))]])
- self.K = controls.dlqr(self.A, self.B, self.Q, self.R)
-
- glog.debug('DT q_pos %f q_vel %s %s', q_pos, q_vel, name)
- glog.debug(str(numpy.linalg.eig(self.A - self.B * self.K)[0]))
- glog.debug('K %s', repr(self.K))
-
- self.hlp = 0.3
- self.llp = 0.4
- self.PlaceObserverPoles([self.hlp, self.hlp, self.llp, self.llp])
-
- self.U_max = numpy.matrix([[12.0], [12.0]])
- self.U_min = numpy.matrix([[-12.0], [-12.0]])
-
- self.InitializeState()
-
-
-class KFDrivetrain(Drivetrain):
- def __init__(self, name="KFDrivetrain", left_low=True, right_low=True):
- super(KFDrivetrain, self).__init__(name, left_low, right_low)
-
- self.unaugmented_A_continuous = self.A_continuous
- self.unaugmented_B_continuous = self.B_continuous
-
- # The practical voltage applied to the wheels is
- # V_left = U_left + left_voltage_error
- #
- # The states are
- # [left position, left velocity, right position, right velocity,
- # left voltage error, right voltage error, angular_error]
- #
- # The left and right positions are filtered encoder positions and are not
- # adjusted for heading error.
- # The turn velocity as computed by the left and right velocities is
- # adjusted by the gyro velocity.
- # The angular_error is the angular velocity error between the wheel speed
- # and the gyro speed.
- self.A_continuous = numpy.matrix(numpy.zeros((7, 7)))
- self.B_continuous = numpy.matrix(numpy.zeros((7, 2)))
- self.A_continuous[0:4,0:4] = self.unaugmented_A_continuous
- self.A_continuous[0:4,4:6] = self.unaugmented_B_continuous
- self.B_continuous[0:4,0:2] = self.unaugmented_B_continuous
- self.A_continuous[0,6] = 1
- self.A_continuous[2,6] = -1
-
- self.A, self.B = self.ContinuousToDiscrete(
- self.A_continuous, self.B_continuous, self.dt)
-
- self.C = numpy.matrix([[1, 0, 0, 0, 0, 0, 0],
- [0, 0, 1, 0, 0, 0, 0],
- [0, -0.5 / self.rb, 0, 0.5 / self.rb, 0, 0, 0]])
-
- self.D = numpy.matrix([[0, 0],
- [0, 0],
- [0, 0]])
-
- q_pos = 0.05
- q_vel = 1.00
- q_voltage = 10.0
- q_encoder_uncertainty = 2.00
-
- self.Q = numpy.matrix([[(q_pos ** 2.0), 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
- [0.0, (q_vel ** 2.0), 0.0, 0.0, 0.0, 0.0, 0.0],
- [0.0, 0.0, (q_pos ** 2.0), 0.0, 0.0, 0.0, 0.0],
- [0.0, 0.0, 0.0, (q_vel ** 2.0), 0.0, 0.0, 0.0],
- [0.0, 0.0, 0.0, 0.0, (q_voltage ** 2.0), 0.0, 0.0],
- [0.0, 0.0, 0.0, 0.0, 0.0, (q_voltage ** 2.0), 0.0],
- [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, (q_encoder_uncertainty ** 2.0)]])
-
- r_pos = 0.0001
- r_gyro = 0.000001
- self.R = numpy.matrix([[(r_pos ** 2.0), 0.0, 0.0],
- [0.0, (r_pos ** 2.0), 0.0],
- [0.0, 0.0, (r_gyro ** 2.0)]])
-
- # Solving for kf gains.
- self.KalmanGain, self.Q_steady = controls.kalman(
- A=self.A, B=self.B, C=self.C, Q=self.Q, R=self.R)
-
- self.L = self.A * self.KalmanGain
-
- unaug_K = self.K
-
- # Implement a nice closed loop controller for use by the closed loop
- # controller.
- self.K = numpy.matrix(numpy.zeros((self.B.shape[1], self.A.shape[0])))
- self.K[0:2, 0:4] = unaug_K
- self.K[0, 4] = 1.0
- self.K[1, 5] = 1.0
-
- self.Qff = numpy.matrix(numpy.zeros((4, 4)))
- qff_pos = 0.005
- qff_vel = 1.00
- self.Qff[0, 0] = 1.0 / qff_pos ** 2.0
- self.Qff[1, 1] = 1.0 / qff_vel ** 2.0
- self.Qff[2, 2] = 1.0 / qff_pos ** 2.0
- self.Qff[3, 3] = 1.0 / qff_vel ** 2.0
- self.Kff = numpy.matrix(numpy.zeros((2, 7)))
- self.Kff[0:2, 0:4] = controls.TwoStateFeedForwards(self.B[0:4,:], self.Qff)
-
- self.InitializeState()
-
+kDrivetrain = drivetrain.DrivetrainParams(J = 6.0,
+ mass = 52,
+ robot_radius = 0.59055 / 2.0,
+ wheel_radius = 0.08255 / 2.0,
+ G_high = 11.0 / 60.0,
+ G_low = 11.0 / 60.0,
+ q_pos_low = 0.12,
+ q_pos_high = 0.14,
+ q_vel_low = 1.0,
+ q_vel_high = 0.95)
def main(argv):
argv = FLAGS(argv)
glog.init()
- # Simulate the response of the system to a step input.
- drivetrain = Drivetrain(left_low=False, right_low=False)
- simulated_left = []
- simulated_right = []
- for _ in xrange(100):
- drivetrain.Update(numpy.matrix([[12.0], [12.0]]))
- simulated_left.append(drivetrain.X[0, 0])
- simulated_right.append(drivetrain.X[2, 0])
-
if FLAGS.plot:
- pylab.rc('lines', linewidth=4)
- pylab.plot(range(100), simulated_left, label='left position')
- pylab.plot(range(100), simulated_right, 'r--', label='right position')
- pylab.suptitle('Acceleration Test\n12 Volt Step Input')
- pylab.legend(loc='lower right')
- pylab.show()
-
- # Simulate forwards motion.
- drivetrain = Drivetrain(left_low=False, right_low=False)
- close_loop_left = []
- close_loop_right = []
- left_power = []
- right_power = []
- R = numpy.matrix([[1.0], [0.0], [1.0], [0.0]])
- for _ in xrange(300):
- U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
- drivetrain.U_min, drivetrain.U_max)
- drivetrain.UpdateObserver(U)
- drivetrain.Update(U)
- close_loop_left.append(drivetrain.X[0, 0])
- close_loop_right.append(drivetrain.X[2, 0])
- left_power.append(U[0, 0])
- right_power.append(U[1, 0])
-
- if FLAGS.plot:
- pylab.plot(range(300), close_loop_left, label='left position')
- pylab.plot(range(300), close_loop_right, 'm--', label='right position')
- pylab.plot(range(300), left_power, label='left power')
- pylab.plot(range(300), right_power, '--', label='right power')
- pylab.suptitle('Linear Move\nLeft and Right Position going to 1')
- pylab.legend()
- pylab.show()
-
- # Try turning in place
- drivetrain = Drivetrain()
- close_loop_left = []
- close_loop_right = []
- R = numpy.matrix([[-1.0], [0.0], [1.0], [0.0]])
- for _ in xrange(200):
- U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
- drivetrain.U_min, drivetrain.U_max)
- drivetrain.UpdateObserver(U)
- drivetrain.Update(U)
- close_loop_left.append(drivetrain.X[0, 0])
- close_loop_right.append(drivetrain.X[2, 0])
-
- if FLAGS.plot:
- pylab.plot(range(200), close_loop_left, label='left position')
- pylab.plot(range(200), close_loop_right, label='right position')
- pylab.suptitle('Angular Move\nLeft position going to -1 and right position going to 1')
- pylab.legend(loc='center right')
- pylab.show()
-
- # Try turning just one side.
- drivetrain = Drivetrain()
- close_loop_left = []
- close_loop_right = []
- R = numpy.matrix([[0.0], [0.0], [1.0], [0.0]])
- for _ in xrange(300):
- U = numpy.clip(drivetrain.K * (R - drivetrain.X_hat),
- drivetrain.U_min, drivetrain.U_max)
- drivetrain.UpdateObserver(U)
- drivetrain.Update(U)
- close_loop_left.append(drivetrain.X[0, 0])
- close_loop_right.append(drivetrain.X[2, 0])
-
- if FLAGS.plot:
- pylab.plot(range(300), close_loop_left, label='left position')
- pylab.plot(range(300), close_loop_right, label='right position')
- pylab.suptitle('Pivot\nLeft position not changing and right position going to 1')
- pylab.legend(loc='center right')
- pylab.show()
-
- # Write the generated constants out to a file.
- drivetrain_low_low = Drivetrain(
- name="DrivetrainLowLow", left_low=True, right_low=True)
- drivetrain_low_high = Drivetrain(
- name="DrivetrainLowHigh", left_low=True, right_low=False)
- drivetrain_high_low = Drivetrain(
- name="DrivetrainHighLow", left_low=False, right_low=True)
- drivetrain_high_high = Drivetrain(
- name="DrivetrainHighHigh", left_low=False, right_low=False)
-
- kf_drivetrain_low_low = KFDrivetrain(
- name="KFDrivetrainLowLow", left_low=True, right_low=True)
- kf_drivetrain_low_high = KFDrivetrain(
- name="KFDrivetrainLowHigh", left_low=True, right_low=False)
- kf_drivetrain_high_low = KFDrivetrain(
- name="KFDrivetrainHighLow", left_low=False, right_low=True)
- kf_drivetrain_high_high = KFDrivetrain(
- name="KFDrivetrainHighHigh", left_low=False, right_low=False)
-
- if len(argv) != 5:
+ drivetrain.PlotDrivetrainMotions(kDrivetrain)
+ elif len(argv) != 5:
print "Expected .h file name and .cc file name"
else:
- namespaces = ['y2017', 'control_loops', 'drivetrain']
- dog_loop_writer = control_loop.ControlLoopWriter(
- "Drivetrain", [drivetrain_low_low, drivetrain_low_high,
- drivetrain_high_low, drivetrain_high_high],
- namespaces = namespaces)
- dog_loop_writer.AddConstant(control_loop.Constant("kDt", "%f",
- drivetrain_low_low.dt))
- dog_loop_writer.AddConstant(control_loop.Constant("kStallTorque", "%f",
- drivetrain_low_low.stall_torque))
- dog_loop_writer.AddConstant(control_loop.Constant("kStallCurrent", "%f",
- drivetrain_low_low.stall_current))
- dog_loop_writer.AddConstant(control_loop.Constant("kFreeSpeed", "%f",
- drivetrain_low_low.free_speed))
- dog_loop_writer.AddConstant(control_loop.Constant("kFreeCurrent", "%f",
- drivetrain_low_low.free_current))
- dog_loop_writer.AddConstant(control_loop.Constant("kJ", "%f",
- drivetrain_low_low.J))
- dog_loop_writer.AddConstant(control_loop.Constant("kMass", "%f",
- drivetrain_low_low.m))
- dog_loop_writer.AddConstant(control_loop.Constant("kRobotRadius", "%f",
- drivetrain_low_low.rb))
- dog_loop_writer.AddConstant(control_loop.Constant("kWheelRadius", "%f",
- drivetrain_low_low.r))
- dog_loop_writer.AddConstant(control_loop.Constant("kR", "%f",
- drivetrain_low_low.resistance))
- dog_loop_writer.AddConstant(control_loop.Constant("kV", "%f",
- drivetrain_low_low.Kv))
- dog_loop_writer.AddConstant(control_loop.Constant("kT", "%f",
- drivetrain_low_low.Kt))
- dog_loop_writer.AddConstant(control_loop.Constant("kLowGearRatio", "%f",
- drivetrain_low_low.G_low))
- dog_loop_writer.AddConstant(control_loop.Constant("kHighGearRatio", "%f",
- drivetrain_high_high.G_high))
- dog_loop_writer.AddConstant(control_loop.Constant("kHighOutputRatio", "%f",
- drivetrain_high_high.G_high * drivetrain_high_high.r))
-
- dog_loop_writer.Write(argv[1], argv[2])
-
- kf_loop_writer = control_loop.ControlLoopWriter(
- "KFDrivetrain", [kf_drivetrain_low_low, kf_drivetrain_low_high,
- kf_drivetrain_high_low, kf_drivetrain_high_high],
- namespaces = namespaces)
- kf_loop_writer.Write(argv[3], argv[4])
+ # Write the generated constants out to a file.
+ drivetrain.WriteDrivetrain(argv[1:3], argv[3:5], 'y2017', kDrivetrain)
if __name__ == '__main__':
sys.exit(main(sys.argv))
diff --git a/y2017/control_loops/python/polydrivetrain.py b/y2017/control_loops/python/polydrivetrain.py
index d3a5683..701308e 100755
--- a/y2017/control_loops/python/polydrivetrain.py
+++ b/y2017/control_loops/python/polydrivetrain.py
@@ -1,13 +1,8 @@
#!/usr/bin/python
-import numpy
import sys
-from frc971.control_loops.python import polytope
from y2017.control_loops.python import drivetrain
-from frc971.control_loops.python import control_loop
-from frc971.control_loops.python import controls
-from frc971.control_loops.python.cim import CIM
-from matplotlib import pylab
+from frc971.control_loops.python import polydrivetrain
import gflags
import glog
@@ -21,479 +16,14 @@
except gflags.DuplicateFlagError:
pass
-def CoerceGoal(region, K, w, R):
- """Intersects a line with a region, and finds the closest point to R.
-
- Finds a point that is closest to R inside the region, and on the line
- defined by K X = w. If it is not possible to find a point on the line,
- finds a point that is inside the region and closest to the line. This
- function assumes that
-
- Args:
- region: HPolytope, the valid goal region.
- K: numpy.matrix (2 x 1), the matrix for the equation [K1, K2] [x1; x2] = w
- w: float, the offset in the equation above.
- R: numpy.matrix (2 x 1), the point to be closest to.
-
- Returns:
- numpy.matrix (2 x 1), the point.
- """
- return DoCoerceGoal(region, K, w, R)[0]
-
-def DoCoerceGoal(region, K, w, R):
- if region.IsInside(R):
- return (R, True)
-
- perpendicular_vector = K.T / numpy.linalg.norm(K)
- parallel_vector = numpy.matrix([[perpendicular_vector[1, 0]],
- [-perpendicular_vector[0, 0]]])
-
- # We want to impose the constraint K * X = w on the polytope H * X <= k.
- # We do this by breaking X up into parallel and perpendicular components to
- # the half plane. This gives us the following equation.
- #
- # parallel * (parallel.T \dot X) + perpendicular * (perpendicular \dot X)) = X
- #
- # Then, substitute this into the polytope.
- #
- # H * (parallel * (parallel.T \dot X) + perpendicular * (perpendicular \dot X)) <= k
- #
- # Substitute K * X = w
- #
- # H * parallel * (parallel.T \dot X) + H * perpendicular * w <= k
- #
- # Move all the knowns to the right side.
- #
- # H * parallel * ([parallel1 parallel2] * X) <= k - H * perpendicular * w
- #
- # Let t = parallel.T \dot X, the component parallel to the surface.
- #
- # H * parallel * t <= k - H * perpendicular * w
- #
- # This is a polytope which we can solve, and use to figure out the range of X
- # that we care about!
-
- t_poly = polytope.HPolytope(
- region.H * parallel_vector,
- region.k - region.H * perpendicular_vector * w)
-
- vertices = t_poly.Vertices()
-
- if vertices.shape[0]:
- # The region exists!
- # Find the closest vertex
- min_distance = numpy.infty
- closest_point = None
- for vertex in vertices:
- point = parallel_vector * vertex + perpendicular_vector * w
- length = numpy.linalg.norm(R - point)
- if length < min_distance:
- min_distance = length
- closest_point = point
-
- return (closest_point, True)
- else:
- # Find the vertex of the space that is closest to the line.
- region_vertices = region.Vertices()
- min_distance = numpy.infty
- closest_point = None
- for vertex in region_vertices:
- point = vertex.T
- length = numpy.abs((perpendicular_vector.T * point)[0, 0])
- if length < min_distance:
- min_distance = length
- closest_point = point
-
- return (closest_point, False)
-
-
-class VelocityDrivetrainModel(control_loop.ControlLoop):
- def __init__(self, left_low=True, right_low=True, name="VelocityDrivetrainModel"):
- super(VelocityDrivetrainModel, self).__init__(name)
- self._drivetrain = drivetrain.Drivetrain(left_low=left_low,
- right_low=right_low)
- self.dt = 0.00505
- self.A_continuous = numpy.matrix(
- [[self._drivetrain.A_continuous[1, 1], self._drivetrain.A_continuous[1, 3]],
- [self._drivetrain.A_continuous[3, 1], self._drivetrain.A_continuous[3, 3]]])
-
- self.B_continuous = numpy.matrix(
- [[self._drivetrain.B_continuous[1, 0], self._drivetrain.B_continuous[1, 1]],
- [self._drivetrain.B_continuous[3, 0], self._drivetrain.B_continuous[3, 1]]])
- self.C = numpy.matrix(numpy.eye(2))
- self.D = numpy.matrix(numpy.zeros((2, 2)))
-
- self.A, self.B = self.ContinuousToDiscrete(self.A_continuous,
- self.B_continuous, self.dt)
-
- # FF * X = U (steady state)
- self.FF = self.B.I * (numpy.eye(2) - self.A)
-
- self.PlaceControllerPoles([0.90, 0.90])
- self.PlaceObserverPoles([0.02, 0.02])
-
- self.G_high = self._drivetrain.G_high
- self.G_low = self._drivetrain.G_low
- self.resistance = self._drivetrain.resistance
- self.r = self._drivetrain.r
- self.Kv = self._drivetrain.Kv
- self.Kt = self._drivetrain.Kt
-
- self.U_max = self._drivetrain.U_max
- self.U_min = self._drivetrain.U_min
-
-
-class VelocityDrivetrain(object):
- HIGH = 'high'
- LOW = 'low'
- SHIFTING_UP = 'up'
- SHIFTING_DOWN = 'down'
-
- def __init__(self):
- self.drivetrain_low_low = VelocityDrivetrainModel(
- left_low=True, right_low=True, name='VelocityDrivetrainLowLow')
- self.drivetrain_low_high = VelocityDrivetrainModel(left_low=True, right_low=False, name='VelocityDrivetrainLowHigh')
- self.drivetrain_high_low = VelocityDrivetrainModel(left_low=False, right_low=True, name = 'VelocityDrivetrainHighLow')
- self.drivetrain_high_high = VelocityDrivetrainModel(left_low=False, right_low=False, name = 'VelocityDrivetrainHighHigh')
-
- # X is [lvel, rvel]
- self.X = numpy.matrix(
- [[0.0],
- [0.0]])
-
- self.U_poly = polytope.HPolytope(
- numpy.matrix([[1, 0],
- [-1, 0],
- [0, 1],
- [0, -1]]),
- numpy.matrix([[12],
- [12],
- [12],
- [12]]))
-
- self.U_max = numpy.matrix(
- [[12.0],
- [12.0]])
- self.U_min = numpy.matrix(
- [[-12.0000000000],
- [-12.0000000000]])
-
- self.dt = 0.00505
-
- self.R = numpy.matrix(
- [[0.0],
- [0.0]])
-
- self.U_ideal = numpy.matrix(
- [[0.0],
- [0.0]])
-
- # ttrust is the comprimise between having full throttle negative inertia,
- # and having no throttle negative inertia. A value of 0 is full throttle
- # inertia. A value of 1 is no throttle negative inertia.
- self.ttrust = 1.0
-
- self.left_gear = VelocityDrivetrain.LOW
- self.right_gear = VelocityDrivetrain.LOW
- self.left_shifter_position = 0.0
- self.right_shifter_position = 0.0
- self.left_cim = CIM()
- self.right_cim = CIM()
-
- def IsInGear(self, gear):
- return gear is VelocityDrivetrain.HIGH or gear is VelocityDrivetrain.LOW
-
- def MotorRPM(self, shifter_position, velocity):
- if shifter_position > 0.5:
- return (velocity / self.CurrentDrivetrain().G_high /
- self.CurrentDrivetrain().r)
- else:
- return (velocity / self.CurrentDrivetrain().G_low /
- self.CurrentDrivetrain().r)
-
- def CurrentDrivetrain(self):
- if self.left_shifter_position > 0.5:
- if self.right_shifter_position > 0.5:
- return self.drivetrain_high_high
- else:
- return self.drivetrain_high_low
- else:
- if self.right_shifter_position > 0.5:
- return self.drivetrain_low_high
- else:
- return self.drivetrain_low_low
-
- def SimShifter(self, gear, shifter_position):
- if gear is VelocityDrivetrain.HIGH or gear is VelocityDrivetrain.SHIFTING_UP:
- shifter_position = min(shifter_position + 0.5, 1.0)
- else:
- shifter_position = max(shifter_position - 0.5, 0.0)
-
- if shifter_position == 1.0:
- gear = VelocityDrivetrain.HIGH
- elif shifter_position == 0.0:
- gear = VelocityDrivetrain.LOW
-
- return gear, shifter_position
-
- def ComputeGear(self, wheel_velocity, should_print=False, current_gear=False, gear_name=None):
- high_omega = (wheel_velocity / self.CurrentDrivetrain().G_high /
- self.CurrentDrivetrain().r)
- low_omega = (wheel_velocity / self.CurrentDrivetrain().G_low /
- self.CurrentDrivetrain().r)
- #print gear_name, "Motor Energy Difference.", 0.5 * 0.000140032647 * (low_omega * low_omega - high_omega * high_omega), "joules"
- high_torque = ((12.0 - high_omega / self.CurrentDrivetrain().Kv) *
- self.CurrentDrivetrain().Kt / self.CurrentDrivetrain().resistance)
- low_torque = ((12.0 - low_omega / self.CurrentDrivetrain().Kv) *
- self.CurrentDrivetrain().Kt / self.CurrentDrivetrain().resistance)
- high_power = high_torque * high_omega
- low_power = low_torque * low_omega
- #if should_print:
- # print gear_name, "High omega", high_omega, "Low omega", low_omega
- # print gear_name, "High torque", high_torque, "Low torque", low_torque
- # print gear_name, "High power", high_power, "Low power", low_power
-
- # Shift algorithm improvements.
- # TODO(aschuh):
- # It takes time to shift. Shifting down for 1 cycle doesn't make sense
- # because you will end up slower than without shifting. Figure out how
- # to include that info.
- # If the driver is still in high gear, but isn't asking for the extra power
- # from low gear, don't shift until he asks for it.
- goal_gear_is_high = high_power > low_power
- #goal_gear_is_high = True
-
- if not self.IsInGear(current_gear):
- glog.debug('%s Not in gear.', gear_name)
- return current_gear
- else:
- is_high = current_gear is VelocityDrivetrain.HIGH
- if is_high != goal_gear_is_high:
- if goal_gear_is_high:
- glog.debug('%s Shifting up.', gear_name)
- return VelocityDrivetrain.SHIFTING_UP
- else:
- glog.debug('%s Shifting down.', gear_name)
- return VelocityDrivetrain.SHIFTING_DOWN
- else:
- return current_gear
-
- def FilterVelocity(self, throttle):
- # Invert the plant to figure out how the velocity filter would have to work
- # out in order to filter out the forwards negative inertia.
- # This math assumes that the left and right power and velocity are equal.
-
- # The throttle filter should filter such that the motor in the highest gear
- # should be controlling the time constant.
- # Do this by finding the index of FF that has the lowest value, and computing
- # the sums using that index.
- FF_sum = self.CurrentDrivetrain().FF.sum(axis=1)
- min_FF_sum_index = numpy.argmin(FF_sum)
- min_FF_sum = FF_sum[min_FF_sum_index, 0]
- min_K_sum = self.CurrentDrivetrain().K[min_FF_sum_index, :].sum()
- # Compute the FF sum for high gear.
- high_min_FF_sum = self.drivetrain_high_high.FF[0, :].sum()
-
- # U = self.K[0, :].sum() * (R - x_avg) + self.FF[0, :].sum() * R
- # throttle * 12.0 = (self.K[0, :].sum() + self.FF[0, :].sum()) * R
- # - self.K[0, :].sum() * x_avg
-
- # R = (throttle * 12.0 + self.K[0, :].sum() * x_avg) /
- # (self.K[0, :].sum() + self.FF[0, :].sum())
-
- # U = (K + FF) * R - K * X
- # (K + FF) ^-1 * (U + K * X) = R
-
- # Scale throttle by min_FF_sum / high_min_FF_sum. This will make low gear
- # have the same velocity goal as high gear, and so that the robot will hold
- # the same speed for the same throttle for all gears.
- adjusted_ff_voltage = numpy.clip(throttle * 12.0 * min_FF_sum / high_min_FF_sum, -12.0, 12.0)
- return ((adjusted_ff_voltage + self.ttrust * min_K_sum * (self.X[0, 0] + self.X[1, 0]) / 2.0)
- / (self.ttrust * min_K_sum + min_FF_sum))
-
- def Update(self, throttle, steering):
- # Shift into the gear which sends the most power to the floor.
- # This is the same as sending the most torque down to the floor at the
- # wheel.
-
- self.left_gear = self.right_gear = True
- if True:
- self.left_gear = self.ComputeGear(self.X[0, 0], should_print=True,
- current_gear=self.left_gear,
- gear_name="left")
- self.right_gear = self.ComputeGear(self.X[1, 0], should_print=True,
- current_gear=self.right_gear,
- gear_name="right")
- if self.IsInGear(self.left_gear):
- self.left_cim.X[0, 0] = self.MotorRPM(self.left_shifter_position, self.X[0, 0])
-
- if self.IsInGear(self.right_gear):
- self.right_cim.X[0, 0] = self.MotorRPM(self.right_shifter_position, self.X[0, 0])
-
- if self.IsInGear(self.left_gear) and self.IsInGear(self.right_gear):
- # Filter the throttle to provide a nicer response.
- fvel = self.FilterVelocity(throttle)
-
- # Constant radius means that angualar_velocity / linear_velocity = constant.
- # Compute the left and right velocities.
- steering_velocity = numpy.abs(fvel) * steering
- left_velocity = fvel - steering_velocity
- right_velocity = fvel + steering_velocity
-
- # Write this constraint in the form of K * R = w
- # angular velocity / linear velocity = constant
- # (left - right) / (left + right) = constant
- # left - right = constant * left + constant * right
-
- # (fvel - steering * numpy.abs(fvel) - fvel - steering * numpy.abs(fvel)) /
- # (fvel - steering * numpy.abs(fvel) + fvel + steering * numpy.abs(fvel)) =
- # constant
- # (- 2 * steering * numpy.abs(fvel)) / (2 * fvel) = constant
- # (-steering * sign(fvel)) = constant
- # (-steering * sign(fvel)) * (left + right) = left - right
- # (steering * sign(fvel) + 1) * left + (steering * sign(fvel) - 1) * right = 0
-
- equality_k = numpy.matrix(
- [[1 + steering * numpy.sign(fvel), -(1 - steering * numpy.sign(fvel))]])
- equality_w = 0.0
-
- self.R[0, 0] = left_velocity
- self.R[1, 0] = right_velocity
-
- # Construct a constraint on R by manipulating the constraint on U
- # Start out with H * U <= k
- # U = FF * R + K * (R - X)
- # H * (FF * R + K * R - K * X) <= k
- # H * (FF + K) * R <= k + H * K * X
- R_poly = polytope.HPolytope(
- self.U_poly.H * (self.CurrentDrivetrain().K + self.CurrentDrivetrain().FF),
- self.U_poly.k + self.U_poly.H * self.CurrentDrivetrain().K * self.X)
-
- # Limit R back inside the box.
- self.boxed_R = CoerceGoal(R_poly, equality_k, equality_w, self.R)
-
- FF_volts = self.CurrentDrivetrain().FF * self.boxed_R
- self.U_ideal = self.CurrentDrivetrain().K * (self.boxed_R - self.X) + FF_volts
- else:
- glog.debug('Not all in gear')
- if not self.IsInGear(self.left_gear) and not self.IsInGear(self.right_gear):
- # TODO(austin): Use battery volts here.
- R_left = self.MotorRPM(self.left_shifter_position, self.X[0, 0])
- self.U_ideal[0, 0] = numpy.clip(
- self.left_cim.K * (R_left - self.left_cim.X) + R_left / self.left_cim.Kv,
- self.left_cim.U_min, self.left_cim.U_max)
- self.left_cim.Update(self.U_ideal[0, 0])
-
- R_right = self.MotorRPM(self.right_shifter_position, self.X[1, 0])
- self.U_ideal[1, 0] = numpy.clip(
- self.right_cim.K * (R_right - self.right_cim.X) + R_right / self.right_cim.Kv,
- self.right_cim.U_min, self.right_cim.U_max)
- self.right_cim.Update(self.U_ideal[1, 0])
- else:
- assert False
-
- self.U = numpy.clip(self.U_ideal, self.U_min, self.U_max)
-
- # TODO(austin): Model the robot as not accelerating when you shift...
- # This hack only works when you shift at the same time.
- if self.IsInGear(self.left_gear) and self.IsInGear(self.right_gear):
- self.X = self.CurrentDrivetrain().A * self.X + self.CurrentDrivetrain().B * self.U
-
- self.left_gear, self.left_shifter_position = self.SimShifter(
- self.left_gear, self.left_shifter_position)
- self.right_gear, self.right_shifter_position = self.SimShifter(
- self.right_gear, self.right_shifter_position)
-
- glog.debug('U is %s %s', str(self.U[0, 0]), str(self.U[1, 0]))
- glog.debug('Left shifter %s %d Right shifter %s %d',
- self.left_gear, self.left_shifter_position,
- self.right_gear, self.right_shifter_position)
-
-
def main(argv):
- vdrivetrain = VelocityDrivetrain()
-
- if not FLAGS.plot:
- if len(argv) != 5:
- glog.fatal('Expected .h file name and .cc file name')
- else:
- namespaces = ['y2017', 'control_loops', 'drivetrain']
- dog_loop_writer = control_loop.ControlLoopWriter(
- "VelocityDrivetrain", [vdrivetrain.drivetrain_low_low,
- vdrivetrain.drivetrain_low_high,
- vdrivetrain.drivetrain_high_low,
- vdrivetrain.drivetrain_high_high],
- namespaces=namespaces)
-
- dog_loop_writer.Write(argv[1], argv[2])
-
- cim_writer = control_loop.ControlLoopWriter("CIM", [CIM()])
-
- cim_writer.Write(argv[3], argv[4])
- return
-
- vl_plot = []
- vr_plot = []
- ul_plot = []
- ur_plot = []
- radius_plot = []
- t_plot = []
- left_gear_plot = []
- right_gear_plot = []
- vdrivetrain.left_shifter_position = 0.0
- vdrivetrain.right_shifter_position = 0.0
- vdrivetrain.left_gear = VelocityDrivetrain.LOW
- vdrivetrain.right_gear = VelocityDrivetrain.LOW
-
- glog.debug('K is %s', str(vdrivetrain.CurrentDrivetrain().K))
-
- if vdrivetrain.left_gear is VelocityDrivetrain.HIGH:
- glog.debug('Left is high')
+ if FLAGS.plot:
+ polydrivetrain.PlotPolyDrivetrainMotions(drivetrain.kDrivetrain)
+ elif len(argv) != 5:
+ glog.fatal('Expected .h file name and .cc file name')
else:
- glog.debug('Left is low')
- if vdrivetrain.right_gear is VelocityDrivetrain.HIGH:
- glog.debug('Right is high')
- else:
- glog.debug('Right is low')
-
- for t in numpy.arange(0, 1.7, vdrivetrain.dt):
- if t < 0.5:
- vdrivetrain.Update(throttle=0.00, steering=1.0)
- elif t < 1.2:
- vdrivetrain.Update(throttle=0.5, steering=1.0)
- else:
- vdrivetrain.Update(throttle=0.00, steering=1.0)
- t_plot.append(t)
- vl_plot.append(vdrivetrain.X[0, 0])
- vr_plot.append(vdrivetrain.X[1, 0])
- ul_plot.append(vdrivetrain.U[0, 0])
- ur_plot.append(vdrivetrain.U[1, 0])
- left_gear_plot.append((vdrivetrain.left_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
- right_gear_plot.append((vdrivetrain.right_gear is VelocityDrivetrain.HIGH) * 2.0 - 10.0)
-
- fwd_velocity = (vdrivetrain.X[1, 0] + vdrivetrain.X[0, 0]) / 2
- turn_velocity = (vdrivetrain.X[1, 0] - vdrivetrain.X[0, 0])
- if abs(fwd_velocity) < 0.0000001:
- radius_plot.append(turn_velocity)
- else:
- radius_plot.append(turn_velocity / fwd_velocity)
-
- # TODO(austin):
- # Shifting compensation.
-
- # Tighten the turn.
- # Closed loop drive.
-
- pylab.plot(t_plot, vl_plot, label='left velocity')
- pylab.plot(t_plot, vr_plot, label='right velocity')
- pylab.plot(t_plot, ul_plot, label='left voltage')
- pylab.plot(t_plot, ur_plot, label='right voltage')
- pylab.plot(t_plot, radius_plot, label='radius')
- pylab.plot(t_plot, left_gear_plot, label='left gear high')
- pylab.plot(t_plot, right_gear_plot, label='right gear high')
- pylab.legend()
- pylab.show()
- return 0
+ polydrivetrain.WritePolyDrivetrain(argv[1:3], argv[3:5], 'y2017',
+ drivetrain.kDrivetrain)
if __name__ == '__main__':
argv = FLAGS(sys.argv)