Example #1
0
    def test_Vertices_Nonsym(self):
        """Tests the vertices of a nonsymetric space."""
        self.k = numpy.matrix([[6], [12], [2], [10]])
        self.p = polytope.HPolytope(self.H, self.k)
        vertices = self.p.Vertices()
        self.AreVertices(self.p, vertices)

        self.HasSamePoints(
            numpy.matrix([[6., 2.], [6., -10.], [-12., -10.], [-12., 2.]]),
            vertices)
Example #2
0
    def test_Skewed_Nonsym_Vertices(self):
        """Tests the vertices of a severely skewed space."""
        self.H = numpy.matrix([[10, -1], [-1, -1], [-1, 10], [10, 10]])
        self.k = numpy.matrix([[2], [2], [2], [2]])
        self.p = polytope.HPolytope(self.H, self.k)
        vertices = self.p.Vertices()
        self.AreVertices(self.p, vertices)

        self.HasSamePoints(
            numpy.matrix([[0., 0.2], [0.2, 0.], [-2., 0.], [0., -2.]]),
            vertices)
  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 = 0.005

    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 = drivetrain.CIM()
    self.right_cim = drivetrain.CIM()
Example #4
0
 def setUp(self):
     """Builds a simple box polytope."""
     self.H = numpy.matrix([[1, 0], [-1, 0], [0, 1], [0, -1]])
     self.k = numpy.matrix([[12], [12], [12], [12]])
     self.p = polytope.HPolytope(self.H, self.k)
Example #5
0
 def MakePWithDims(self, num_constraints, num_dims):
     """Makes a zeroed out polytope with the correct size."""
     self.p = polytope.HPolytope(
         numpy.matrix(numpy.zeros((num_constraints, num_dims))),
         numpy.matrix(numpy.zeros((num_constraints, 1))))
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)
  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)