forked from Telos4/RoboRally
rewrote pid controller to derive from ControllerBase. works with multiple robots now
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parent
2060d8eb15
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35b6c3bdfd
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@ -2,9 +2,12 @@ import numpy as np
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import math
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import time
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class PIDController:
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def __init__(self, event_listener):
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self.t = time.time()
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from controller import ControllerBase
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class PIDController(ControllerBase):
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def __init__(self):
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super().__init__()
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self.t = None
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self.controlling = False
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@ -16,177 +19,100 @@ class PIDController:
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self.I_pos = 0.3
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self.D_pos = 0.1
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self.mode = None
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self.mode = 'combined'
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self.event_listener = event_listener
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self.e_angle_old = 0.0
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self.e_pos_old = 0.0
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def control_multiple_robots(self, robots):
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robot_target_positions = {}
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for robot in robots:
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robot_target_positions[robot.id] = None
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self.i = 0.0
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self.i_angle = 0.0
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self.i_pos = 0.0
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running = True
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while running:
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pass
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def set_target_position(self, target_pos):
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super(PIDController, self).set_target_position(target_pos)
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self.mode = 'combined'
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self.e_angle_old = 0.0
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self.e_pos_old = 0.0
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self.i = 0.0
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self.i_angle = 0.0
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self.i_pos = 0.0
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def interactive_control(self, robots):
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controlled_robot_number = 0
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robot = robots[controlled_robot_number]
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def compute_control(self, state):
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# measure state
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x_pred = state[1:]
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ts = []
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angles = []
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if self.t is None:
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dt = 0.1
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else:
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dt = time.time() - self.t
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target_pos = np.array([0.0, 0.0, 0.0])
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e_angle_old = 0.0
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e_pos_old = 0.0
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#print(f"x_pred = {x_pred}\ntarget = {target_pos}\nerror = {np.linalg.norm(target_pos - x_pred)}\n")
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if self.mode == 'angle':
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# compute angle such that robot faces to target point
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target_angle = self.target_pos[2]
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i = 0.0
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i_angle = 0.0
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i_pos = 0.0
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angles_unwrapped = np.unwrap([x_pred[2], target_angle]) # unwrap angle to avoid jump in data
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t0 = time.time()
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e_angle = angles_unwrapped[0] - angles_unwrapped[1] # angle difference
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p = self.P_angle * e_angle
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# i += self.I * dt * e # right Riemann sum
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self.i += self.I_angle * dt * (e_angle + self.e_angle_old)/2.0 # trapezoidal rule
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d = self.D_angle * (e_angle - self.e_angle_old)/dt
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running = True
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while running:
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# handle events from opencv window
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while not self.event_listener.event_queue.empty():
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event = self.event_listener.event_queue.get()
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print("event: ", event)
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if event[0] == 'click':
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target = event[1]
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target_pos = np.array([target['x'], target['y'], target['angle']])
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i_angle = 0
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i_pos = 0
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e_pos_old = 0
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e_angle_old = 0
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self.mode = 'combined'
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elif event[0] == 'key':
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key = event[1]
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u1 = p + self.i + d
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u2 = - u1
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if key == 32: # arrow up
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self.controlling = not self.controlling
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if not self.controlling:
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print("disable control")
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robot.send_cmd() # stop robot
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self.mode = None # reset control mode
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else:
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print("enable control")
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i = 0
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self.t = time.time()
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elif key == 48: # 0
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target_pos = np.array([0.0, 0.0, 0.0]) # TODO: use center of board for target pos
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elif key == 97: # a
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self.mode = 'angle'
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e_angle_old = 0
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i = 0
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self.t = time.time()
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elif key == 99: # c
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self.mode = 'combined'
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e_angle_old = 0
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e_pos_old = 0
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i_angle = 0
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i_pos = 0
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self.t = time.time()
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elif key == 112: # p
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self.mode = 'position'
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e_pos_old = 0
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i = 0
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self.t = time.time()
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elif key == 43: # +
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self.P_pos += 0.1
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print("P = ", self.P_angle)
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elif key == 45: # -
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self.P_pos -= 0.1
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print("P = ", self.P_angle)
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elif key == 9: # TAB
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# switch controlled robot
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robot.send_cmd() # stop current robot
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controlled_robot_number = (controlled_robot_number + 1) % len(robots)
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robot = robots[controlled_robot_number]
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print(f"controlled robot: {robot.id}")
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elif key == 113 or key == 27: # q or ESCAPE
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print("quit!")
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self.controlling = False
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robot.send_cmd()
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return
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self.e_angle_old = e_angle
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if self.controlling:
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# measure state
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t, x, y, angle = robot.get_measurement()
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x_pred = np.array([x, y, angle])
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dt = self.t - time.time()
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elif self.mode == 'combined':
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# compute angle such that robot faces to target point
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v = self.target_pos[0:2] - x_pred[0:2]
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target_angle = math.atan2(v[1], v[0])
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#print(f"x_pred = {x_pred}\ntarget = {target_pos}\nerror = {np.linalg.norm(target_pos - x_pred)}\n")
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if self.mode == 'angle':
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# compute angle such that robot faces to target point
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target_angle = target_pos[2]
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angles_unwrapped = np.unwrap([x_pred[2], target_angle]) # unwrap angle to avoid jump in data
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ts.append(time.time() - t0)
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angles.append(x_pred[2])
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e_angle = angles_unwrapped[0] - angles_unwrapped[1] # angle difference
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e_pos = np.linalg.norm(v)
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angles_unwrapped = np.unwrap([x_pred[2], target_angle]) # unwrap angle to avoid jump in data
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if e_pos < 0.05:
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self.mode = 'angle'
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self.e_angle_old = 0
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self.e_pos_old = 0
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self.i_angle = 0
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self.i_pos = 0
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u1 = 0
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u2 = 0
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else:
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forward = abs(e_angle) < np.pi/2.0
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e_angle = angles_unwrapped[0] - angles_unwrapped[1] # angle difference
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p = self.P_angle * e_angle
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# i += self.I * dt * e # right Riemann sum
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i += self.I_angle * dt * (e_angle + e_angle_old)/2.0 # trapezoidal rule
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d = self.D_angle * (e_angle - e_angle_old)/dt
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u1 = p - i - d
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u2 = - u1
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e_angle_old = e_angle
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elif self.mode == 'combined':
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# compute angle such that robot faces to target point
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v = target_pos[0:2] - x_pred[0:2]
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target_angle = math.atan2(v[1], v[0])
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angles_unwrapped = np.unwrap([x_pred[2], target_angle]) # unwrap angle to avoid jump in data
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e_angle = angles_unwrapped[0] - angles_unwrapped[1] # angle difference
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e_pos = np.linalg.norm(v)
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if e_pos < 0.05:
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self.mode = 'angle'
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e_angle_old = 0
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e_pos_old = 0
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i_angle = 0
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i_pos = 0
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u1 = 0
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u2 = 0
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if not forward:
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if e_angle > np.pi/2.0:
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e_angle -= np.pi
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else:
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forward = abs(e_angle) < np.pi/2.0
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e_angle += np.pi
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if not forward:
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if e_angle > np.pi/2.0:
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e_angle -= np.pi
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else:
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e_angle += np.pi
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p_angle = self.P_angle * e_angle
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self.i_angle += self.I_angle * dt * (e_angle + self.e_angle_old) / 2.0 # trapezoidal rule
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d_angle = self.D_angle * (e_angle - self.e_angle_old) / dt
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p_angle = self.P_angle * e_angle
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i_angle += self.I_angle * dt * (e_angle + e_angle_old) / 2.0 # trapezoidal rule
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d_angle = self.D_angle * (e_angle - e_angle_old) / dt
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p_pos = self.P_pos * e_pos
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i_pos += self.I_pos * dt * (e_pos + e_pos_old) / 2.0 # trapezoidal rule
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d_pos = self.D_pos * (e_pos - e_pos_old) / dt
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if forward:
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u1 = p_angle + p_pos - i_angle - i_pos - d_angle - d_pos
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u2 = - p_angle + p_pos + i_angle - i_pos + d_angle - d_pos
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else:
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u1 = p_angle - p_pos - i_angle + i_pos - d_angle + d_pos
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u2 = - p_angle - p_pos + i_angle + i_pos + d_angle + d_pos
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e_pos_old = e_pos
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e_angle_old = e_angle
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p_pos = self.P_pos * e_pos
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self.i_pos += self.I_pos * dt * (e_pos + self.e_pos_old) / 2.0 # trapezoidal rule
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d_pos = self.D_pos * (e_pos - self.e_pos_old) / dt
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if forward:
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u1 = p_angle + p_pos + self.i_angle + self.i_pos + d_angle + d_pos
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u2 = - p_angle + p_pos - self.i_angle + self.i_pos - d_angle + d_pos
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else:
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u1 = 0.0
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u2 = 0.0
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#print(f"u = ({u1}, {u2})")
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robot.send_cmd(u1, u2)
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self.t = time.time() # save time when the most recent control was applied
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time.sleep(0.05)
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u1 = p_angle - p_pos + self.i_angle - self.i_pos + d_angle - d_pos
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u2 = - p_angle - p_pos - self.i_angle - self.i_pos - d_angle - d_pos
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self.e_pos_old = e_pos
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self.e_angle_old = e_angle
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else:
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u1 = 0.0
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u2 = 0.0
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#print(f"u = ({u1}, {u2})")
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self.t = time.time() # save time when the most recent control was applied
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return (u1, u2)
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