Update bot3 drivetrain and get defense bot working.
Change-Id: I0e3d5c0e768ee77eaeaf0a963f15c3172389ea6e
diff --git a/y2014_bot3/control_loops/python/drivetrain.py b/y2014_bot3/control_loops/python/drivetrain.py
index 4231887..b0555a0 100755
--- a/y2014_bot3/control_loops/python/drivetrain.py
+++ b/y2014_bot3/control_loops/python/drivetrain.py
@@ -4,10 +4,16 @@
from frc971.control_loops.python import controls
import numpy
import sys
+import argparse
from matplotlib import pylab
+import gflags
import glog
+FLAGS = gflags.FLAGS
+
+gflags.DEFINE_bool('plot', False, 'If true, plot the loop response.')
+
class CIM(control_loop.ControlLoop):
def __init__(self):
super(CIM, self).__init__("CIM")
@@ -22,10 +28,10 @@
# Moment of inertia of the CIM in kg m^2
self.J = 0.0001
# Resistance of the motor, divided by 2 to account for the 2 motors
- self.R = 12.0 / self.stall_current
+ self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = ((self.free_speed / 60.0 * 2.0 * numpy.pi) /
- (12.0 - self.R * self.free_current))
+ (12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current
# Control loop time step
@@ -33,9 +39,9 @@
# State feedback matrices
self.A_continuous = numpy.matrix(
- [[-self.Kt / self.Kv / (self.J * self.R)]])
+ [[-self.Kt / self.Kv / (self.J * self.resistance)]])
self.B_continuous = numpy.matrix(
- [[self.Kt / (self.J * self.R)]])
+ [[self.Kt / (self.J * self.resistance)]])
self.C = numpy.matrix([[1]])
self.D = numpy.matrix([[0]])
@@ -54,36 +60,34 @@
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.stall_torque = 2.42 * self.num_motors * 0.60
# Stall Current in Amps
- self.stall_current = 133.0
+ self.stall_current = 133.0 * self.num_motors
# Free Speed in RPM. Used number from last year.
- self.free_speed = 4650.0
+ self.free_speed = 5500.0
# Free Current in Amps
- self.free_current = 2.7
+ self.free_current = 4.7 * self.num_motors
# Moment of inertia of the drivetrain in kg m^2
- # Just borrowed from last year.
- self.J = 10
+ self.J = 1.8
# Mass of the robot, in kg.
- self.m = 68
- # Radius of the robot, in meters (from last year).
- self.rb = 0.9603 / 2.0
+ self.m = 37
+ # Radius of the robot, in meters (requires tuning by hand)
+ self.rb = 0.601 / 2.0
# Radius of the wheels, in meters.
self.r = 0.0508
# Resistance of the motor, divided by the number of motors.
- self.R = 12.0 / self.stall_current / 2
+ self.resistance = 12.0 / self.stall_current
# Motor velocity constant
self.Kv = ((self.free_speed / 60.0 * 2.0 * numpy.pi) /
- (12.0 - self.R * self.free_current))
+ (12.0 - self.resistance * self.free_current))
# Torque constant
self.Kt = self.stall_torque / self.stall_current
# Gear ratios
- self.G_const = 18.0 / 44.0 * 18.0 / 60.0
-
- self.G_low = self.G_const
- self.G_high = self.G_const
-
+ self.G_low = 28.0 / 60.0 * 19.0 / 50.0
+ self.G_high = 28.0 / 48.0 * 19.0 / 50.0
if left_low:
self.Gl = self.G_low
else:
@@ -101,10 +105,10 @@
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.R * self.r * self.r)
- self.tcr = -self.Kt / self.Kv / (self.Gr * self.Gr * self.R * self.r * self.r)
- self.mpl = self.Kt / (self.Gl * self.R * self.r)
- self.mpr = self.Kt / (self.Gr * self.R * self.r)
+ 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
@@ -124,17 +128,16 @@
self.D = numpy.matrix([[0, 0],
[0, 0]])
- #glog.debug('THE NUMBER I WANT %s', str(numpy.linalg.inv(self.A_continuous) * -self.B_continuous * numpy.matrix([[12.0], [12.0]])))
self.A, self.B = self.ContinuousToDiscrete(
self.A_continuous, self.B_continuous, self.dt)
- # Poles from last year.
- self.hp = 0.65
- self.lp = 0.83
- self.PlaceControllerPoles([self.hp, self.lp, self.hp, self.lp])
- glog.info('K %s', str(self.K))
- q_pos = 0.07
- q_vel = 1.0
+ if left_low or right_low:
+ q_pos = 0.12
+ q_vel = 1.0
+ else:
+ q_pos = 0.14
+ q_vel = 0.95
+
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],
@@ -143,10 +146,10 @@
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.info('A %s', str(self.A))
- glog.info('B %s', str(self.B))
- glog.info('K %s', str(self.K))
- glog.info('Poles are %s', str(numpy.linalg.eig(self.A - self.B * self.K)[0]))
+
+ 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
@@ -154,11 +157,102 @@
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 states are
+ # The practical voltage applied to the wheels is
+ # V_left = U_left + left_voltage_error
+ #
+ # [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()
+
+
def main(argv):
+ argv = FLAGS(argv)
+ glog.init()
+
# Simulate the response of the system to a step input.
- drivetrain = Drivetrain()
+ drivetrain = Drivetrain(left_low=False, right_low=False)
simulated_left = []
simulated_right = []
for _ in xrange(100):
@@ -166,26 +260,37 @@
simulated_left.append(drivetrain.X[0, 0])
simulated_right.append(drivetrain.X[2, 0])
- #pylab.plot(range(100), simulated_left)
- #pylab.plot(range(100), simulated_right)
- #pylab.show()
+ 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()
+ 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(100):
+ 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(100), close_loop_left)
- #pylab.plot(range(100), close_loop_right)
- #pylab.show()
+ 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()
@@ -200,9 +305,11 @@
close_loop_left.append(drivetrain.X[0, 0])
close_loop_right.append(drivetrain.X[2, 0])
- #pylab.plot(range(100), close_loop_left)
- #pylab.plot(range(100), close_loop_right)
- #pylab.show()
+ 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()
@@ -217,25 +324,75 @@
close_loop_left.append(drivetrain.X[0, 0])
close_loop_right.append(drivetrain.X[2, 0])
- #pylab.plot(range(100), close_loop_left)
- #pylab.plot(range(100), close_loop_right)
- #pylab.show()
+ 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.
- glog.info('Output one')
- 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)
+ 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)
- if len(argv) != 3:
- glog.fatal('Expected .h file name and .cc file name')
+ 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:
+ print "Expected .h file name and .cc file name"
else:
+ namespaces = ['y2014_bot3', 'control_loops', 'drivetrain']
dog_loop_writer = control_loop.ControlLoopWriter(
"Drivetrain", [drivetrain_low_low, drivetrain_low_high,
drivetrain_high_low, drivetrain_high_high],
- namespaces=['y2014_bot3', 'control_loops', 'drivetrain'])
+ 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("kFreeSpeedRPM", "%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.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])
+
if __name__ == '__main__':
sys.exit(main(sys.argv))