Code:

import gymimport numpy as npfrom urdfenvs.robots.tiago import TiagoRobotfrom urdfenvs.robots.generic_urdf import GenericUrdfReacherfrom urdfenvs.robots.prius import Prius# import sys# sys.path.append("/home/josyula/Programs/MAS_Project/gym_envs_urdf/")import pybulletdef run_multi_robot(n_steps=1000, render=False, obstacles=False, goal=False):    robots = [        GenericUrdfReacher(urdf="pointRobot.urdf", mode="vel"),        GenericUrdfReacher(urdf="pointRobot.urdf", mode="vel"),        # GenericUrdfReacher(urdf="ur5.urdf", mode="acc"),        # GenericUrdfReacher(urdf="ur5.urdf", mode="acc"),        # TiagoRobot(mode="vel"),        # Prius(mode="vel")    ]    env = gym.make(        "urdf-env-v0",        dt=0.01, robots=robots, render=render    )    n = env.n()    action = np.ones(n) * -0.2    pos0 = np.zeros(n)    pos0[1] = -0.0    base_pos = np.array([        [0.0, 1.0, 0.0],        [0.0, -1.0, 0.0],        [0.0, -2.0, 0.0]        ])    ob = env.reset(pos=pos0, base_pos=base_pos)    print(f"Initial observation : {ob}")    if goal:        from examples.scene_objects.goal import dynamicGoal        env.add_goal(dynamicGoal)    # if obstacles:    #     from examples.scene_objects.obstacles import dynamicSphereObst2    #     env.add_obstacle(dynamicSphereObst2)    pybullet.createVisualShape(pybullet.GEOM_BOX, halfExtents=[0.5, 0.5, 0.5])    print("Starting episode")    history = []    for _ in range(n_steps):        ob, _, _, _ = env.step(action)        history.append(ob)    env.close()    return history    #add load onto robotsif __name__ == "__main__":    run_multi_robot(render=True, obstacles=True, goal=True)