import asyncio import json import random from ulab import numpy as np import arena import robot class Simulation: def __init__(self): population_size = 10 # x, y, heading self.poses = np.empty((population_size, 3), dtype=np.float) for n in range(population_size): self.poses[n] = random.uniform(0, arena.width), random.uniform(0, arena.height), random.uniform(0, 360) def move_poses(self, speed_in_mm, heading_change): for pose in self.poses: pose[2] += heading_change pose[2] = pose[2] % 360 pose[0] += speed_in_mm * np.cos(np.radians(pose[2])) pose[1] += speed_in_mm * np.sin(np.radians(pose[2])) def eliminate_impossible_poses(self, left_distance, right_distance): poses_to_keep = np.ones(len(self.poses), dtype=np.uint8) # todo: would reorganising these pose arrays let us better use ulab tools? for position, pose in enumerate(self.poses): # first those outside the arena keep = arena.point_is_inside_arena((pose[0], pose[1])) if keep: left_distance_origin = pose[0] + robot.distance_sensor_from_middle * np.cos(np.radians(pose[2] + 90)), pose[1] + robot.distance_sensor_from_middle * np.sin(np.radians(pose[2] + 90)) right_distance_origin = pose[0] + robot.distance_sensor_from_middle * np.cos(np.radians(pose[2] - 90)), pose[1] + robot.distance_sensor_from_middle * np.sin(np.radians(pose[2] - 90)) left_distance_end = left_distance_origin[0] + left_distance * np.cos(np.radians(pose[2])), left_distance_origin[1] + left_distance * np.sin(np.radians(pose[2])) right_distance_end = right_distance_origin[0] + right_distance * np.cos(np.radians(pose[2])), right_distance_origin[1] + right_distance * np.sin(np.radians(pose[2])) keep = arena.point_is_inside_arena(left_distance_end) and arena.point_is_inside_arena(right_distance_end) poses_to_keep[position] = int(keep) # apply the keep as a mask to the poses using ulab. - doesn't work in ulab. self.poses = np.array([item for item, keep in zip(self.poses, poses_to_keep) if keep]) async def run(self): try: robot.left_distance.start_ranging() robot.right_distance.start_ranging() for _ in range(5): starting_heading = robot.imu.euler[0] encoder_left = robot.left_encoder.read() encoder_right = robot.right_encoder.read() robot.set_left(1) robot.set_right(0.5) await asyncio.sleep(0.1) left_movement = robot.left_encoder.read() - encoder_left right_movement = robot.right_encoder.read() - encoder_right # move poses speed_in_mm = robot.ticks_to_m * ((left_movement + right_movement) / 2) * 1000 new_heading = robot.imu.euler[0] heading_change = starting_heading - new_heading self.move_poses(speed_in_mm, heading_change) if robot.left_distance.data_ready and robot.right_distance.data_ready: left_distance = robot.left_distance.distance * 10 # convert to mm right_distance = robot.right_distance.distance * 10 self.eliminate_impossible_poses(left_distance, right_distance) robot.left_distance.clear_interrupt() robot.right_distance.clear_interrupt() finally: robot.stop() def send_json(data): robot.uart.write((json.dumps(data)+"\n").encode()) async def command_handler(simulation): simulation_task = None while True: if robot.uart.in_waiting: print("Receiving data...") try: data = robot.uart.readline().decode() request = json.loads(data) except (UnicodeError, ValueError): print("Invalid data") continue # {"command": "arena"} if request["command"] == "arena": send_json({ "arena": arena.boundary_lines, "target_zone": arena.target_zone, }) elif request["command"] == "start": print("Starting simulation") if simulation_task is None or simulation_task.done(): simulation_task = asyncio.create_task(simulation.run()) elif request["command"] == "stop": robot.stop() if simulation_task and not simulation_task.done(): simulation_task.cancel() simulation_task = None else: sys_status, gyro, accel, mag = robot.imu.calibration_status if sys_status != 3: send_json({"imu_calibration": { "gyro": gyro, "accel": accel, "mag": mag, "sys": sys_status, }}) else: send_json({ "poses": simulation.poses.tolist(), }) await asyncio.sleep(0.1) simulation= Simulation() asyncio.run(command_handler(simulation))