Merge remote-tracking branch 'origin/main' into user/rcadene/2024_09_04_feetech
This commit is contained in:
@@ -11,7 +11,7 @@ This tutorial will guide you through the process of setting up and training a ne
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By following these steps, you'll be able to replicate tasks like picking up a Lego block and placing it in a bin with a high success rate, as demonstrated in [this video](https://x.com/RemiCadene/status/1814680760592572934).
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This tutorial is specifically made for the affordable [Koch v1.1](https://github.com/jess-moss/koch-v1-1) robot, but it contains additional information to be easily adapted to various types of robots like [Aloha bimanual robot](aloha-2.github.io) by changing some configurations. The Koch v1.1 consists of a leader arm and a follower arm, each with 6 motors. It can work with one or several cameras to record the scene, which serve as visual sensors for the robot.
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This tutorial is specifically made for the affordable [Koch v1.1](https://github.com/jess-moss/koch-v1-1) robot, but it contains additional information to be easily adapted to various types of robots like [Aloha bimanual robot](https://aloha-2.github.io) by changing some configurations. The Koch v1.1 consists of a leader arm and a follower arm, each with 6 motors. It can work with one or several cameras to record the scene, which serve as visual sensors for the robot.
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During the data collection phase, you will control the follower arm by moving the leader arm. This process is known as "teleoperation." This technique is used to collect robot trajectories. Afterward, you'll train a neural network to imitate these trajectories and deploy the network to enable your robot to operate autonomously.
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@@ -32,7 +32,7 @@ git clone https://github.com/huggingface/lerobot.git ~/lerobot
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5. Install LeRobot with dependencies for the Aloha motors (dynamixel) and cameras (intelrealsense):
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```bash
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cd ~/lerobot && pip install -e ".[dynamixel intelrealsense]"
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cd ~/lerobot && pip install -e ".[dynamixel, intelrealsense]"
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```
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For Linux only (not Mac), install extra dependencies for recording datasets:
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@@ -196,19 +196,19 @@ def say(text, blocking=False):
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# Check if mac, linux, or windows.
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if platform.system() == "Darwin":
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cmd = f'say "{text}"'
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if not blocking:
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cmd += " &"
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elif platform.system() == "Linux":
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cmd = f'spd-say "{text}"'
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if blocking:
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cmd += " --wait"
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elif platform.system() == "Windows":
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# TODO(rcadene): Make blocking option work for Windows
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cmd = (
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'PowerShell -Command "Add-Type -AssemblyName System.Speech; '
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f"(New-Object System.Speech.Synthesis.SpeechSynthesizer).Speak('{text}')\""
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)
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if not blocking and platform.system() in ["Darwin", "Linux"]:
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# TODO(rcadene): Make it work for Windows
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# Use the ampersand to run command in the background
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cmd += " &"
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os.system(cmd)
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2
poetry.lock
generated
2
poetry.lock
generated
@@ -7441,4 +7441,4 @@ xarm = ["gym-xarm"]
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[metadata]
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lock-version = "2.0"
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python-versions = ">=3.10,<3.13"
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content-hash = "6c4bdf158f8744a5ba190df7e02bf4cdd545daa0680ef019706581e514c9e198"
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content-hash = "7ff63d36a5524a77cba916d212741082adcb49dfdc0dc49f8bf8ccee53c02254"
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@@ -44,7 +44,8 @@ diffusers = ">=0.27.2"
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torchvision = ">=0.17.1"
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h5py = ">=3.10.0"
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huggingface-hub = {extras = ["hf-transfer", "cli"], version = ">=0.25.0"}
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gymnasium = ">=0.29.1"
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# TODO(rcadene, aliberts): Make gym 1.0.0 work
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gymnasium = "==0.29.1"
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cmake = ">=3.29.0.1"
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gym-dora = { git = "https://github.com/dora-rs/dora-lerobot.git", subdirectory = "gym_dora", optional = true }
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gym-pusht = { version = ">=0.1.5", optional = true}
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