Moved Drivetrain from y2017_bot3 python to frc971
Change-Id: Ie7bb94c839ff1483d53a60abb2164a87f662cf4e
diff --git a/y2017_bot3/control_loops/python/BUILD b/y2017_bot3/control_loops/python/BUILD
index ab4b383..0209757 100644
--- a/y2017_bot3/control_loops/python/BUILD
+++ b/y2017_bot3/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'],
)
diff --git a/y2017_bot3/control_loops/python/drivetrain.py b/y2017_bot3/control_loops/python/drivetrain.py
index 846fc39..6b5ea65 100755
--- a/y2017_bot3/control_loops/python/drivetrain.py
+++ b/y2017_bot3/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
@@ -13,348 +10,29 @@
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 = 2.7 * self.num_motors
- #TODO(Neil): Update robot moment of inertia, mass, and robot radius
- # 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 = 4 * 0.0254 / 2
- # 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 = 14.0 / 40.0 * 24.0 / 60.0 * 52.0 / 60.0
- self.G_high = 14.0 / 40.0 * 34.0 / 50.0 * 52.0 / 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()
-
+#TODO(Neil): Update robot moment of inertia, mass, and robot radius
+kDrivetrain = drivetrain.DrivetrainParams(J = 6.0,
+ mass = 52,
+ robot_radius = 0.59055 / 2.0,
+ wheel_radius = 4 * 0.0254 / 2,
+ G_high = 14.0 / 40.0 * 34.0 / 50.0 * 52.0 / 60.0,
+ G_low = 14.0 / 40.0 * 24.0 / 60.0 * 52.0 / 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.plot(range(100), simulated_left)
- pylab.plot(range(100), simulated_right)
- pylab.suptitle('Acceleration Test')
- 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, 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')
- 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(100):
- 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(100), close_loop_left)
- pylab.plot(range(100), close_loop_right)
- pylab.suptitle('Angular Move')
- 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(100):
- 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(100), close_loop_left)
- pylab.plot(range(100), close_loop_right)
- pylab.suptitle('Pivot')
- 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_bot3', '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_bot3', kDrivetrain)
if __name__ == '__main__':
sys.exit(main(sys.argv))
diff --git a/y2017_bot3/control_loops/python/polydrivetrain.py b/y2017_bot3/control_loops/python/polydrivetrain.py
index 59ba5cd..92aa6e4 100755
--- a/y2017_bot3/control_loops/python/polydrivetrain.py
+++ b/y2017_bot3/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_bot3.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_bot3', '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_bot3',
+ drivetrain.kDrivetrain)
if __name__ == '__main__':
argv = FLAGS(sys.argv)