""" 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. Apply Forces (apply_forces.py) ---------------------------- This example shows how to apply forces and torques to rigid bodies using the tensor API. """ from isaacgym import gymutil from isaacgym import gymapi from isaacgym import gymtorch import numpy as np import torch # initialize gym gym = gymapi.acquire_gym() # parse arguments args = gymutil.parse_arguments( description="Example of applying forces and torques to bodies") # configure sim sim_params = gymapi.SimParams() sim_params.up_axis = gymapi.UP_AXIS_Z sim_params.gravity = gymapi.Vec3(0.0, 0.0, -9.81) if args.physics_engine == gymapi.SIM_PHYSX: sim_params.substeps = 1 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 elif args.physics_engine == gymapi.SIM_FLEX and not args.use_gpu_pipeline: sim_params.flex.shape_collision_margin = 0.25 sim_params.flex.num_outer_iterations = 4 sim_params.flex.num_inner_iterations = 10 else: raise Exception("GPU pipeline is only available with PhysX") sim_params.use_gpu_pipeline = args.use_gpu_pipeline device = args.sim_device if args.use_gpu_pipeline else 'cpu' sim = gym.create_sim(args.compute_device_id, args.graphics_device_id, args.physics_engine, sim_params) if sim is None: raise Exception("Failed to create sim") # add ground plane plane_params = gymapi.PlaneParams() plane_params.normal = gymapi.Vec3(0, 0, 1) gym.add_ground(sim, plane_params) # create viewer viewer = gym.create_viewer(sim, gymapi.CameraProperties()) if viewer is None: raise Exception("Failed to create viewer") # load ball asset asset_root = "../../assets" asset_file = "mjcf/nv_ant.xml" asset = gym.load_asset(sim, asset_root, asset_file, gymapi.AssetOptions()) num_bodies = gym.get_asset_rigid_body_count(asset) print('num_bodies', num_bodies) # default pose pose = gymapi.Transform() pose.p.z = 1.0 # set up the env grid num_envs = 4 num_per_row = int(np.sqrt(num_envs)) env_spacing = 2.0 env_lower = gymapi.Vec3(-env_spacing, -env_spacing, 0.0) env_upper = gymapi.Vec3(env_spacing, env_spacing, env_spacing) # set random seed np.random.seed(17) envs = [] handles = [] for i in range(num_envs): # create env env = gym.create_env(sim, env_lower, env_upper, num_per_row) envs.append(env) # generate random bright color c = 0.5 + 0.5 * np.random.random(3) color = gymapi.Vec3(c[0], c[1], c[2]) ahandle = gym.create_actor(env, asset, pose, "actor", i, 1) handles.append(ahandle) gym.set_rigid_body_color(env, ahandle, 0, gymapi.MESH_VISUAL_AND_COLLISION, color) gym.viewer_camera_look_at(viewer, None, gymapi.Vec3(20, 20, 5), gymapi.Vec3(0, 0, 1)) gym.prepare_sim(sim) torque_amt = 100 frame_count = 0 while not gym.query_viewer_has_closed(viewer): if (frame_count - 99) % 200 == 0: # set forces and torques for the ant root bodies forces = torch.zeros((num_envs, num_bodies, 3), device=device, dtype=torch.float) torques = torch.zeros((num_envs, num_bodies, 3), device=device, dtype=torch.float) forces[:, 0, 2] = 300 torques[:, 0, 2] = torque_amt gym.apply_rigid_body_force_tensors(sim, gymtorch.unwrap_tensor(forces), gymtorch.unwrap_tensor(torques), gymapi.ENV_SPACE) torque_amt = -torque_amt # step the physics gym.simulate(sim) gym.fetch_results(sim, True) # update the viewer gym.step_graphics(sim) gym.draw_viewer(viewer, sim, True) # Wait for dt to elapse in real time. # This synchronizes the physics simulation with the rendering rate. gym.sync_frame_time(sim) frame_count += 1 gym.destroy_viewer(viewer) gym.destroy_sim(sim)