def plan_act(self, obs):
nn_obs = self.transform_obs(obs)
nn_action = self.agent.act(nn_obs)
steering_angle = self.max_steer * nn_action[0]
speed = calculate_speed(steering_angle)
action = np.array([steering_angle, speed])
return action
def plan_act(self, obs):
scan = obs[7:-1]
ranges = np.array(scan, dtype=np.float)
steering_angle = self.process_lidar(ranges)
steering_angle = steering_angle * np.pi / 180
# speed = 4
speed = calculate_speed(steering_angle)
action = np.array([steering_angle, speed])
return action
def plan_act(self, obs):
nn_obs = self.transform_obs(obs)
self.add_memory_entry(obs, nn_obs)
nn_action = self.agent.act(nn_obs)
self.state = obs
self.nn_state = nn_obs
self.nn_action = nn_action
steering_angle = self.max_steer * nn_action[0]
speed = calculate_speed(steering_angle)
self.action = np.array([steering_angle, speed])
return self.action
def act_pp(self, obs):
pose_th = obs[2]
pos = np.array(obs[0:2], dtype=np.float)
lookahead_point = self._get_current_waypoint(pos)
self.aim_pts.append(lookahead_point[0:2])
if lookahead_point is None:
return [0, 4.0]
speed, steering_angle = pure_pursuit_utils.get_actuation(
pose_th, lookahead_point, pos, self.lookahead, self.wheelbase)
speed = calculate_speed(steering_angle)
return [steering_angle, speed]
def plan_act(self, obs):
pp_action = super().act_pp(obs)
nn_obs = self.transform_obs(obs, pp_action)
self.add_memory_entry(obs, nn_obs)
self.state = obs
nn_action = self.agent.act(nn_obs)
self.nn_act = nn_action
# critic_val = self.agent.get_critic_value(nn_obs, nn_action)
# self.history.add_step(pp_action[0], nn_action[0]*self.max_steer, critic_val)
self.nn_state = nn_obs
steering_angle = self.modify_references(self.nn_act, pp_action[0])
# speed = 4
speed = calculate_speed(steering_angle)
self.action = np.array([steering_angle, speed])
return self.action
def plan_act(self, obs):
pp_action = super().act_pp(obs)
nn_obs = self.transform_obs(obs, pp_action)
nn_action = self.agent.act(nn_obs, noise=0)
# nn_action = [0]
self.nn_act = nn_action
critic_val = self.agent.get_critic_value(nn_obs, nn_action)
self.history.add_step(pp_action[0], nn_action[0]*self.max_steer, critic_val)
steering_angle = self.modify_references(self.nn_act, pp_action[0])
# speed = 4
speed = calculate_speed(steering_angle)
action = np.array([steering_angle, speed])
# pp = pp_action[0]/self.max_steer
# self.vis.add_step(nn_obs[4:], pp, nn_action)
return action