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Functions490 in github.com/AirHockeyChallenge/air_hockey_challenge

⨍ Functions 490◇ Types & classes 89
↓ 22 callersMethodupdate
(self)
air_hockey_challenge/utils/universal_joint_plugin.py:46
↓ 19 callersFunctionforward_kinematics
Compute the forward kinematics of the robots. IMPORTANT: For the iiwa we assume that the universal joint at the end of the end-effec
air_hockey_challenge/utils/kinematics.py:5
↓ 14 callersMethodget_puck
Getting the puck properties from the observations Args: obs: The current observation Returns: ([pos_
air_hockey_challenge/environments/iiwas/env_base.py:236
↓ 13 callersMethodkeys
(self)
air_hockey_challenge/constraints/constraints.py:96
↓ 12 callersMethodadd
(self, c)
air_hockey_challenge/constraints/constraints.py:102
↓ 12 callersMethodreset
(self, obs)
baseline/ppo_baseline_agent/agent.py:69
↓ 12 callersMethodupdate
(self, measurement, predicted_state, P)
baseline/baseline_agent/kalman_filter.py:190
↓ 11 callersFunctionjacobian
Compute the Jacobian of the robots. IMPORTANT: For the iiwa we assume that the universal joint at the end of the end-effector always
air_hockey_challenge/utils/kinematics.py:93
↓ 10 callersMethodreset
(self, state=None)
air_hockey_challenge/framework/air_hockey_challenge_wrapper.py:81
↓ 9 callersMethod_set_tactic
(self, tactic)
baseline/baseline_agent/tactics.py:42
↓ 9 callersMethodcompute_control_point
(self, p_start, v_start, p_stop, v_stop, t_plan=None)
baseline/baseline_agent/bezier_planner.py:19
↓ 9 callersFunctioninverse_kinematics
Compute the inverse kinematics of the robots. IMPORTANT: For the iiwa we assume that the universal joint at the end of the end-effec
air_hockey_challenge/utils/kinematics.py:42
↓ 8 callersMethodfun
The function of the constraint. Args ---- q: numpy.ndarray, (num_joints,) The joint position of the robo
air_hockey_challenge/constraints/constraints.py:40
↓ 8 callersMethodgenerate_bezier_trajectory
(self, max_steps=-1)
baseline/baseline_agent/trajectory_generator.py:55
↓ 8 callersMethodget_joint_pos
Get the joint position from the observation. Args ---- obs: numpy.ndarray Agent's observation.
air_hockey_challenge/framework/agent_base.py:157
↓ 8 callersMethodget_puck
(self, obs: jax.Array)
air_hockey_challenge/environments/brax_envs/env_base.py:420
↓ 8 callersMethodseed
(self, seed: int = 0)
baseline/ppo_baseline_agent/utils/brax_wrapper.py:80
↓ 8 callersMethodupdate_bezier_curve
(self, t_start, p_stop, v_stop, t_final)
baseline/baseline_agent/bezier_planner_new.py:157
↓ 7 callersMethod_round_time
(self, time)
baseline/baseline_agent/bezier_planner.py:151
↓ 7 callersFunctionf
(q)
air_hockey_challenge/utils/mjx/kinematics.py:73
↓ 7 callersMethodoptimize_trajectory
(self, cart_traj, q_start, dq_start, q_anchor)
baseline/baseline_agent/optimizer.py:25
↓ 7 callersMethodrender
(self, mode: str = "human")
baseline/ppo_baseline_agent/utils/brax_wrapper.py:83
↓ 6 callersMethod_get_from_socket
(self, socket, operation, obs=None)
air_hockey_challenge/utils/tournament_agent_wrapper.py:127
↓ 6 callersMethod_puck_2d_in_robot_frame
(puck_in, robot_frame, type='pose')
air_hockey_challenge/environments/iiwas/env_base.py:214
↓ 6 callersMethoddraw_action
(self, obs)
baseline/ppo_baseline_agent/agent.py:29
↓ 6 callersMethodget_puck_pos
Get the Puck's position from the observation. Args ---- obs: numpy.ndarray Agent's observation.
air_hockey_challenge/framework/agent_base.py:123
↓ 6 callersMethodget_time_bezier_root
(self, t)
baseline/baseline_agent/bezier_planner_new.py:134
↓ 6 callersMethodpredict
(self, state, P)
baseline/baseline_agent/kalman_filter.py:179
↓ 6 callersMethodrender
(self, record=False)
air_hockey_challenge/framework/air_hockey_challenge_wrapper.py:78
↓ 5 callersMethodfun
The function of the constraint. Args ---- q: jnp.ndarray, (num_joints,) The joint position of the robot
air_hockey_challenge/constraints/brax_constraints.py:44
↓ 5 callersMethodget
(self, key)
air_hockey_challenge/constraints/constraints.py:99
↓ 5 callersMethodget_joint_vel
Get the joint velocity from the observation. Args ---- obs: numpy.ndarray Agent's observation.
air_hockey_challenge/framework/agent_base.py:174
↓ 5 callersMethodget_point
(self, t)
baseline/baseline_agent/bezier_planner.py:114
↓ 5 callersMethodjacobian
Jacobian is the derivative of the constraint function w.r.t the robot joint position and velocity. Args ---- q: jnp.
air_hockey_challenge/constraints/brax_constraints.py:75
↓ 5 callersMethodstep
(self, action)
air_hockey_challenge/framework/air_hockey_challenge_wrapper.py:58
↓ 5 callersMethodstop
(self)
examples/control/hitting_agent.py:280
↓ 4 callersMethod__init__
Constructor Args ---- env_info: dict A dictionary contains information about the environment; ou
air_hockey_challenge/constraints/constraints.py:9
↓ 4 callersMethod__init__
Constructor Args ---- env_info: Dict A dictionary contains information about the environment; ou
air_hockey_challenge/constraints/brax_constraints.py:11
↓ 4 callersMethod_round_time
(self, time)
baseline/baseline_agent/bezier_planner_new.py:203
↓ 4 callersMethodcan_smash
(self)
baseline/baseline_agent/tactics.py:49
↓ 4 callersMethoddraw_action
(self, state)
air_hockey_challenge/utils/tournament_agent_wrapper.py:22
↓ 4 callersMethodget_closest_point_from_line_to_point
(l0, l1, p, range=None)
baseline/baseline_agent/bezier_planner_new.py:207
↓ 4 callersMethodget_point
(self, t)
baseline/baseline_agent/bezier_planner_new.py:120
↓ 4 callersMethodget_prediction
(self, t, defend_line=0.)
baseline/baseline_agent/kalman_filter.py:205
↓ 4 callersMethodjacobian
Jacobian is the derivative of the constraint function w.r.t the robot joint position and velocity. Args ---- q: ndar
air_hockey_challenge/constraints/constraints.py:62
↓ 4 callersFunctionlink_to_xml_name
(mj_model, link)
air_hockey_challenge/utils/kinematics.py:127
↓ 4 callersMethodreset
(self, rng: jax.Array)
air_hockey_challenge/environments/brax_envs/env_base.py:248
↓ 3 callersMethod_create_traj
(self, state, action, i=0)
air_hockey_challenge/environments/brax_position_control_wrapper.py:210
↓ 3 callersMethod_create_traj
(self, interp_order, action, i=0)
air_hockey_challenge/environments/position_control_wrapper.py:203
↓ 3 callersMethod_cross_2d
(self, u, v)
baseline/baseline_agent/kalman_filter.py:128
↓ 3 callersMethod_get_from_socket
(self, socket, operation, obs=None)
air_hockey_challenge/utils/tournament_agent_wrapper.py:183
↓ 3 callersMethod_get_obs
(self, data: mjx.Data)
air_hockey_challenge/environments/brax_envs/env_base.py:360
↓ 3 callersMethod_puck_pose_2d_in_robot_frame
Convert puck position from world frame to robot frame. puck_in: Puck position in world frame (x, y, z). robot_frame: Robot ba
air_hockey_challenge/environments/brax_envs/env_base.py:427
↓ 3 callersMethod_puck_vel_2d_in_robot_frame
( puck_in: jax.Array, robot_frame: jax.Array )
air_hockey_challenge/environments/brax_envs/env_base.py:453
↓ 3 callersFunction_run_tournament
( log_dir, agent_builder, name_1, name_2, n_steps=45000, n_episodes=10, n_cores=-1
air_hockey_challenge/framework/evaluate_tournament.py:402
↓ 3 callersMethodcheck_success
(self, obs)
air_hockey_challenge/framework/air_hockey_challenge_wrapper.py:87
↓ 3 callersMethodgenerate_bezier_trajectory
(self, max_steps=-1)
examples/control/hitting_agent.py:236
↓ 3 callersMethodget_ee
(self)
air_hockey_challenge/environments/iiwas/env_base.py:254
↓ 3 callersMethodis_puck_stuck
(self)
baseline/baseline_agent/tactics.py:72
↓ 3 callersFunctionnumerical_grad
(fun, q)
baseline/baseline_agent/optimizer.py:183
↓ 3 callersMethodreset
(self)
examples/control/hitting_agent.py:82
↓ 3 callersMethodreset
(self)
examples/control/defending_agent.py:65
↓ 3 callersMethodshould_defend
(self)
baseline/baseline_agent/tactics.py:57
↓ 3 callersMethodstep
(self, measurement)
baseline/baseline_agent/kalman_filter.py:200
↓ 3 callersMethodstep
(self, state: State, action: jax.Array)
baseline/ppo_baseline_agent/modified_envs/env_base.py:42
↓ 3 callersMethodupdate_ee_pos_vel
(self, joint_pos, joint_vel)
baseline/baseline_agent/system_state.py:138
↓ 3 callersMethodupdate_prediction
(self, prediction_time, stop_line=0.)
baseline/baseline_agent/system_state.py:134
↓ 2 callersMethod__init__
(self, env_info, path)
baseline/ppo_baseline_agent/agent.py:21
↓ 2 callersMethod__init__
(self, p_gain, d_gain, i_gain, interpolation_order=3, *args, **kwargs)
air_hockey_challenge/environments/brax_position_control_wrapper.py:11
↓ 2 callersMethod__init__
Mixin that adds position controller to mujoco environments. Args: p_gain (float): Proportional controller ga
air_hockey_challenge/environments/position_control_wrapper.py:12
↓ 2 callersMethod_control_universal_joint
(self, state: State)
air_hockey_challenge/environments/brax_envs/env_base.py:511
↓ 2 callersMethod_control_universal_joint
(self)
air_hockey_challenge/utils/universal_joint_plugin.py:49
↓ 2 callersMethod_create_observation
(self, state: State, obs: jax.Array)
air_hockey_challenge/environments/brax_envs/env_base.py:395
↓ 2 callersMethod_cross_3d
(self, a, b)
air_hockey_challenge/environments/brax_envs/env_base.py:619
↓ 2 callersMethod_cross_3d
(self, a, b)
air_hockey_challenge/utils/universal_joint_plugin.py:119
↓ 2 callersMethod_default_opponent_action_gen
(self)
air_hockey_challenge/environments/position_control_wrapper.py:250
↓ 2 callersMethod_fk
(self, pos)
baseline/ppo_baseline_agent/modified_envs/env_base.py:141
↓ 2 callersMethod_fun
(self, q, dq)
air_hockey_challenge/constraints/constraints.py:85
↓ 2 callersMethod_fun
(self, q, dq)
air_hockey_challenge/constraints/brax_constraints.py:107
↓ 2 callersMethod_jacobian
(self, q, dq)
air_hockey_challenge/constraints/constraints.py:88
↓ 2 callersMethod_modify_observation
(self, obs: jax.Array)
air_hockey_challenge/environments/brax_envs/env_base.py:398
↓ 2 callersFunctionagent_builder
( mdp, i, build_agent_1, build_agent_2, agent_1_kwargs, agent_2_kwargs )
air_hockey_challenge/framework/evaluate_tournament.py:74
↓ 2 callersMethodcompute_time_bezier
(self, dz_start, dz_stop, t_plan)
baseline/baseline_agent/bezier_planner_new.py:95
↓ 2 callersMethodcubic_spline_interpolation
(self, joint_pos_traj)
examples/control/defending_agent.py:172
↓ 2 callersMethoddelete
(self, name)
air_hockey_challenge/constraints/constraints.py:105
↓ 2 callersMethoddraw_action
Draw an action, i.e., desired joint position and velocity, at every time step. Args: observation (ndarray): Observed state inclu
air_hockey_challenge/framework/agent_base.py:44
↓ 2 callersMethodepisode_start
(self)
air_hockey_challenge/framework/agent_base.py:61
↓ 2 callersMethodget_closest_point_between_line_segments
(l1s, l1e, l2s, l2e, range=None)
baseline/baseline_agent/bezier_planner_new.py:217
↓ 2 callersMethodget_ee_pose
Get the End-Effector's Position from the observation. Args ---- obs: numpy.ndarray Agent's observation.
air_hockey_challenge/framework/agent_base.py:191
↓ 2 callersMethodget_joints
(self, obs)
air_hockey_challenge/environments/iiwas/env_base.py:257
↓ 2 callersMethodget_time_bezier_root
(self, t)
baseline/baseline_agent/bezier_planner.py:128
↓ 2 callersFunctionget_violations
(n_steps, episode_size, constraints_dict, computation_time)
air_hockey_challenge/framework/evaluate_tournament.py:648
↓ 2 callersMethodis_puck_static
(self)
baseline/baseline_agent/system_state.py:96
↓ 2 callersMethodmodify_obs
(self, state: State)
baseline/ppo_baseline_agent/modified_envs/env_base.py:156
↓ 2 callersMethodplan_cubic_linear_motion
(self, start_pos, start_vel, end_pos, end_vel, t_total=None)
baseline/baseline_agent/trajectory_generator.py:49
↓ 2 callersMethodpuck_in_success_region
(self, puck_pos, puck_vel)
baseline/ppo_baseline_agent/modified_envs/env_prepare.py:40
↓ 2 callersFunctionreplay_dataset
( env_name, dataset_path, agent_name="Agent", opponent_name="Opponent", viewer_params={},
air_hockey_challenge/utils/replay_dataset.py:9
↓ 2 callersFunctionrobot_to_world
Transform position or rotation optional from the robot base frame to the world frame Args ---- base_frame: numpy.ndarray, (4,4)
air_hockey_challenge/utils/transformations.py:4
↓ 2 callersFunctionrun_remote_tournament
Run a tournament game between two docker containers with the team names name_1 and name_2. The images have to be pulled beforehand. Args
air_hockey_challenge/framework/evaluate_tournament.py:231
↓ 2 callersFunctionrun_tournament
Run tournament games between two agents which are build by build_agent_1 and build_agent_2. The resulting Dataset and constraint stats will b
air_hockey_challenge/framework/evaluate_tournament.py:33
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