# Configuration for ManipTrans (IsaacGym) dynamics retargeting pipeline defaults: - _self_ # Dataset configuration dataset_dir: "example_datasets" dataset_name: "maniptrans" robot_type: "inspire" # "inspire", "shadow", "allegro", "xhand" embodiment_type: "left" # "right", "left", "bimanual" task: "0f900@0" # HO-Tracker data index used as task name (format: sequence_id@sub_id) data_id: 0 seed: 0 viewer: "none" # "isaac" for isaac gym native viewer rerun_spawn: false device: "cuda:0" # Simulation and control parameters simulator: maniptrans sim_dt: 0.0166667 # 1/60 second (IsaacGym default) ctrl_dt: 0.2 # Control timestep (how often MPC updates) knot_dt: 0.2 # Knot point spacing ref_dt: 0.0166667 # Reference trajectory timestep render_dt: 0.0166667 # Same as sim_dt trace_dt: 0.0166667 # Must be divisible by sim_dt horizon: 0.6 # MPC horizon in seconds show_viewer: false save_video: true save_info: true max_sim_steps: -1 # -1 means use full trajectory length nu: 18 # 6 (wrist force/torque) + 12 (inspire DOFs), overridden by env # MPC optimization parameters max_num_iterations: 32 # Number of iterations per MPC step num_samples: 1024 # Number of parallel samples for CEM last_ctrl_noise_scale: 1.0 first_ctrl_noise_scale: 0.5 final_noise_scale: 0.1 # this part is handled by base controller in maniptrans pos_noise_scale: 0.0 rot_noise_scale: 0.0 joint_noise_scale: 1.0 improvement_threshold: 0.001 improvement_check_steps: 4 terminal_rew_scale: 10.0 temperature: 1.0 # Domain randomization (not used for ManipTrans evaluation) num_dr: 1 # ManipTrans-specific parameters (maniptrans_data_indices derived from task name) maniptrans_episode_length: 1200 maniptrans_tighten_method: "None" # No curriculum tightening for MPC maniptrans_tighten_factor: 1.0 maniptrans_tighten_steps: 3200 maniptrans_actions_moving_average: 0.4 maniptrans_use_pid: false maniptrans_use_quat_rot: false maniptrans_ctrl_freq_inv: 1 maniptrans_record_video: false # Record video after MPC (replay with 2-env camera) # Output configuration (empty = use standard path under dataset_dir) output_dir: ""