forked from Telos4/RoboRally
103 lines
4.0 KiB
Python
103 lines
4.0 KiB
Python
import numpy as np
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import time
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from casadi_opt import OpenLoopSolver
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class MPCController:
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def __init__(self, estimator):
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self.t = time.time()
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self.estimator = estimator
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self.controlling = False
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self.mstep = 2
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self.ols = OpenLoopSolver(N=20, T=1.0)
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self.ols.setup()
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self.dt = self.ols.T / self.ols.N
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# integrator
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self.omega_max = 5.0
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self.control_scaling = 0.2
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def move_to_pos(self, target_pos, robot, near_target_counter=5):
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near_target = 0
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while near_target < near_target_counter:
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while not self.estimator.event_queue.empty():
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event = self.estimator.event_queue.get()
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print("event: ", event)
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if event[0] == 'click':
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pass
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elif event[0] == 'key':
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key = event[1]
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if key == 84: # arrow up
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self.controlling = True
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self.t = time.time()
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elif key == 82: # arrow down
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self.controlling = False
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robot.send_cmd()
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elif key == 48: # 0
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target_pos = np.array([0.0,0.0,0.0])
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elif key == 43: # +
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self.control_scaling += 0.1
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self.control_scaling = min(self.control_scaling, 1.0)
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print("control scaling = ", self.control_scaling)
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elif key == 45: # -
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self.control_scaling -= 0.1
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self.control_scaling = max(self.control_scaling, 0.1)
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print("control scaling = ", self.control_scaling)
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elif key == 113:
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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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elif key == 27: # 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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self.anim_stopped = True
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return
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x_pred = self.get_measurement(robot.id)
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error_pos = np.linalg.norm(x_pred[0:2] - target_pos[0:2])
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angles_unwrapped = np.unwrap([x_pred[2], target_pos[2]]) # unwrap angle to avoid jump in data
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error_ang = np.abs(angles_unwrapped[0] - angles_unwrapped[1])
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#print("error pos = ", error_pos)
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#print("error_pos = {}, error_ang = {}".format(error_pos, error_ang))
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#if error_pos > 0.075 or error_ang > 0.35:
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if error_pos > 0.05 or error_ang > 0.2:
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# solve mpc open loop problem
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res = self.ols.solve(x_pred, target_pos)
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#us1 = res[0]
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#us2 = res[1]
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us1 = res[0] * self.control_scaling
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us2 = res[1] * self.control_scaling
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#print("u = {}", (us1, us2))
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tmpc_end = time.time()
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#print("---------------- mpc solution took {} seconds".format(tmpc_end - tmpc_start))
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dt_mpc = time.time() - self.t
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if dt_mpc < self.dt: # wait until next control can be applied
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#print("sleeping for {} seconds...".format(self.dt - dt_mpc))
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time.sleep(self.dt - dt_mpc)
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else:
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us1 = [0] * self.mstep
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us2 = [0] * self.mstep
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near_target += 1
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# send controls to the robot
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for i in range(0, self.mstep): # option to use multistep mpc if len(range) > 1
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u1 = us1[i]
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u2 = us2[i]
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robot.send_cmd(u1, u2)
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if i < self.mstep:
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time.sleep(self.dt)
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self.t = time.time() # save time the most recent control was applied
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def get_measurement(self, robot_id):
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return np.array(self.estimator.get_robot_state_estimate(robot_id))
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