""" Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved. NVIDIA CORPORATION and its licensors retain all intellectual property and proprietary rights in and to this software, related documentation and any modifications thereto. Any use, reproduction, disclosure or distribution of this software and related documentation without an express license agreement from NVIDIA CORPORATION is strictly prohibited. Domain Randomization Example ---------------------------- An example that demonstrates domain randomization. - Randomize color - Randomize texture - Randomize light parameters - Randomize camera position """ import os import random from isaacgym import gymapi from isaacgym import gymutil # initialize gym gym = gymapi.acquire_gym() # parse arguments args = gymutil.parse_arguments( description="Domain Randomization Example", headless=True, custom_parameters=[ {"name": "--save_images", "action": "store_true", "help": "Store Images To Disk"}]) # configure sim sim_params = gymapi.SimParams() sim_params.substeps = 2 sim_params.dt = 1.0 / 60.0 if args.physics_engine == gymapi.SIM_FLEX: pass else: sim_params.physx.solver_type = 1 sim_params.physx.num_position_iterations = 4 sim_params.physx.num_velocity_iterations = 1 sim_params.physx.num_threads = args.num_threads sim_params.physx.use_gpu = args.use_gpu sim_params.use_gpu_pipeline = False if args.use_gpu_pipeline: print("WARNING: Forcing CPU pipeline.") sim = gym.create_sim(args.compute_device_id, args.graphics_device_id, args.physics_engine, sim_params) if sim is None: print("*** Failed to create sim") quit() # add ground plane plane_params = gymapi.PlaneParams() gym.add_ground(sim, gymapi.PlaneParams()) # create viewer if not args.headless: viewer = gym.create_viewer(sim, gymapi.CameraProperties()) if viewer is None: raise ValueError('*** Failed to create viewer') # set up the env grid num_envs = 1 spacing = 0.75 env_lower = gymapi.Vec3(-spacing, 0.0, -spacing) env_upper = gymapi.Vec3(spacing, spacing, spacing) # create ant asset asset_root = "../../assets" asset_file = "mjcf/nv_ant.xml" print("Loading asset '%s' from '%s'" % (asset_file, asset_root)) ant_asset = gym.load_asset(sim, asset_root, asset_file) if ant_asset is None: raise IOError("Failed to load asset") envs = [] actor_handles = [] camera_handles = [] # Load textures from file texture_files = os.listdir("../../assets/textures/") loaded_texture_handle_list = [] for file in texture_files: if file.endswith(".jpg"): loaded_texture_handle_list.append(gym.create_texture_from_file(sim, os.path.join("../../assets/textures/", file))) # Sensor camera properties cam_pos = gymapi.Vec3(0.0, 3.0, 3.0) cam_target = gymapi.Vec3(0.0, 0.0, -1.0) cam_props = gymapi.CameraProperties() cam_props.width = 360 cam_props.height = 360 # Create environments print('Creating %d environments' % num_envs) for i in range(num_envs): # create env env = gym.create_env(sim, env_lower, env_upper, 2) envs.append(env) # create ant actor pose = gymapi.Transform() pose.p = gymapi.Vec3(0, 0.5, 0) pose.r = gymapi.Quat(-0.707107, 0.0, 0.0, 0.707107) ahandle = gym.create_actor(env, ant_asset, pose, 'ant', i, 1) actor_handles.append(ahandle) # configure DOF properties to move freely props = gym.get_actor_dof_properties(env, ahandle) props["driveMode"].fill(gymapi.DOF_MODE_NONE) props["stiffness"].fill(0.0) props["damping"].fill(0.0) gym.set_actor_dof_properties(env, ahandle, props) # create camera actor camera_handle = gym.create_camera_sensor(env, cam_props) camera_handles.append(camera_handle) body = gym.get_actor_rigid_body_handle(env, ahandle, 0) gym.attach_camera_to_body(camera_handle, env, body, gymapi.Transform(p=cam_pos), gymapi.FOLLOW_TRANSFORM) gym.set_camera_location(camera_handle, env, cam_pos, cam_target) # position viewer camera if not args.headless: gym.viewer_camera_look_at(viewer, None, cam_pos, cam_target) sequence_number = 0 # Only create the folder if it doesn't exist if not os.path.exists('dr_output_images'): os.mkdir("dr_output_images") while True: # step the physics gym.simulate(sim) gym.fetch_results(sim, True) # render camera sensor gym.render_all_camera_sensors(sim) # update graphics transforms gym.step_graphics(sim) if not args.headless: # render the viewer gym.draw_viewer(viewer, sim, True) # Wait for dt to elapse in real time to sync viewer with # simulation rate. Not necessary in headless. gym.sync_frame_time(sim) # Check for exit condition - user closed the viewer window if gym.query_viewer_has_closed(viewer): break # randomize body color/texture to box actors and env lights every 100 frames if gym.get_frame_count(sim) % 100 == 0: for i in range(num_envs): env = envs[i] # randomize sensor camera position y_offset = random.uniform(-1.0, 1.0) z_offset = random.uniform(-1.0, 1.0) cam_pos_new = cam_pos + gymapi.Vec3(0., y_offset, z_offset) gym.set_camera_location(camera_handles[i], env, cam_pos_new, cam_target) # randomize colors and textures for rigid body num_bodies = gym.get_actor_rigid_body_count(env, actor_handles[-1]) for n in range(num_bodies): gym.set_rigid_body_color(env, actor_handles[-1], n, gymapi.MESH_VISUAL, gymapi.Vec3(random.uniform(0, 1), random.uniform(0, 1), random.uniform(0, 1))) gym.set_rigid_body_texture(env, actor_handles[-1], n, gymapi.MESH_VISUAL, loaded_texture_handle_list[random.randint(0, len(loaded_texture_handle_list)-1)]) # randomize light parameters l_color = gymapi.Vec3(random.uniform(1, 1), random.uniform(1, 1), random.uniform(1, 1)) l_ambient = gymapi.Vec3(random.uniform(0, 1), random.uniform(0, 1), random.uniform(0, 1)) l_direction = gymapi.Vec3(random.uniform(0, 1), random.uniform(0, 1), random.uniform(0, 1)) gym.set_light_parameters(sim, 0, l_color, l_ambient, l_direction) # save rgb image to disk if args.save_images: print("writing dr_output_images/rgb_image_%03d_%03d.png" % (sequence_number, i)) rgb_image_filename = "dr_output_images/rgb_image_%03d_%03d.png" % (sequence_number, i) gym.write_camera_image_to_file(sim, env, camera_handle, gymapi.IMAGE_COLOR, rgb_image_filename) sequence_number = sequence_number + 1 print('Done') if not args.headless: gym.destroy_viewer(viewer) gym.destroy_sim(sim)