Changed bounds for a new so100 robot
Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com>
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@ -8,7 +8,8 @@
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# env.gym.obs_type=environment_state_agent_pos \
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seed: 1
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dataset_repo_id: aractingi/push_cube_square_light_offline_demo_cropped_resized
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dataset_repo_id: aractingi/push_cube_square_offline_demo_cropped_resized
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#aractingi/push_cube_square_light_offline_demo_cropped_resized
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training:
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# Offline training dataloader
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@ -88,8 +89,8 @@ policy:
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# min: [-1.0, -1.0, -1.0, -1.0, -1.0, -1.0]
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# max: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
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action:
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min: [-145.283203125, -69.43359375, -78.75, -46.0546875]
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max: [145.283203125, 69.43359375, 78.75, 46.0546875]
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min: [-149.23828125, -97.734375, -100.1953125, -73.740234375]
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max: [149.23828125, 97.734375, 100.1953125, 73.740234375]
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# Architecture / modeling.
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# Neural networks.
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@ -14,14 +14,9 @@ calibration_dir: .cache/calibration/so100
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# Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
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# the number of motors in your follower arms.
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max_relative_target: null
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joint_position_relative_bounds:
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min: [-87.09961, 62.402344, 67.23633, 36.035156, 77.34375,
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0.53691274]
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max: [58.183594, 131.83594, 145.98633, 82.08984, 78.22266,
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0.60402685]
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# min: [-88.50586, 23.81836, 0.87890625, -32.16797, 78.66211, 0.53691274]
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# max: [84.55078, 187.11914, 145.98633, 101.60156, 146.60156, 88.18792]
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joint_position_relative_bounds:
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max: [ 7.2158203e+01, 1.5398438e+02, 1.6075195e+02, 9.3251953e+01, 0., -1.4184397e-01]
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min: [-77.08008, 56.25, 60.55664, 19.511719, 0., -0.63829786]
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leader_arms:
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main:
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@ -39,7 +34,7 @@ leader_arms:
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follower_arms:
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main:
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_target_: lerobot.common.robot_devices.motors.feetech.FeetechMotorsBus
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port: /dev/tty.usbmodem585A0080971
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port: /dev/tty.usbmodem58760431631
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motors:
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# name: (index, model)
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shoulder_pan: [1, "sts3215"]
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@ -239,7 +239,7 @@ if __name__ == "__main__":
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)
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args = parser.parse_args()
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dataset = LeRobotDataset(repo_id=args.repo_id, root=args.root, local_files_only=True)
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dataset = LeRobotDataset(repo_id=args.repo_id, root=args.root, local_files_only=False)
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images = get_image_from_lerobot_dataset(dataset)
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images = {k: v.cpu().permute(1, 2, 0).numpy() for k, v in images.items()}
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