Mobile Manipulation with LeKiwi and PincOpen

The article presents a detailed account of assembling and upgrading a LeKiwi mobile manipulator integrated with a PincOpen parallel gripper, focusing on resolving technical challenges and optimizing performance for real-world tasks. The author shares insights on overcoming issues such as servo failures during forward stretches by implementing a 3D-printed support block, adjusting P-gain settings, and upgrading to stronger STS3250 servos. The integration with LeRobot 0.5.2 is highlighted, emphasizing modifications to support the LeKiwi system, including a dual-teleoperation setup and customized camera configurations. The article also explores the impact of data scaling, inference modes, and fine-tuning on task performance, revealing that unfreezing the vision language model (VLM) improved navigation capabilities. The author concludes by suggesting the use of torchcodec for video processing and hints at future explorations in multi-task learning and reinforcement learning to enhance robotic capabilities.

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