storm_kit.mpc.model.urdf_kinematic_model module

class URDFKinematicModel(urdf_path, dt, batch_size=1000, horizon=5, tensor_args={'device': 'cpu', 'dtype': torch.float32}, ee_link_name='ee_link', link_names=[], dt_traj_params=None, vel_scale=0.5, control_space='acc')[source]

Bases: storm_kit.mpc.model.model_base.DynamicsModelBase

_abc_impl = <_abc_data object>
enforce_bounds(state_batch)[source]

Project state into bounds

get_next_state(curr_state: torch.Tensor, act: torch.Tensor, dt)[source]

Does a single step from the current state Args: curr_state: current state act: action dt: time to integrate Returns: next_state

integrate_action(act_seq)[source]
integrate_action_step(act, dt)[source]
render(state)[source]
render_trajectory(state_list)[source]
rollout_open_loop(start_state: torch.Tensor, act_seq: torch.Tensor, dt=None)Tuple[torch.Tensor, torch.Tensor, torch.Tensor][source]
tensor_step(state: torch.Tensor, act: torch.Tensor, state_seq: torch.Tensor, dt=None)torch.Tensor[source]

Args: state: [1,N] act: [H,N] todo: Integration with variable dt along trajectory