Scalable, Intuitive, Mixed Reality-Based Semi-Autonomous Robotic Telemanipulation for the Execution of a Fine-Grained Bimanual Task

Key points

• Recently, semi-autonomous robotic telemanipulation has emerged as a promising direction that reduces operator workload while preserving human-in-the-loop control for task execution.1
• We therefore introduce a scalable, intuitive, semi-autonomous robotic telemanipulation system that leverages a mixed reality (MR) headset for on-robot data collection.1
• We validate the effectiveness of our system by collecting data and training imitation learning policies on the execution of a high-precision, fine-grained bimanual peg-in-hole task.1
• With lower data collection effort, our system obtains high-quality demonstrations that can be used to train fully autonomous task execution policies.1

Sources (1)

• [1]Scalable, Intuitive, Mixed Reality-Based Semi-Autonomous Robotic Telemanipulation for the Execution of a Fine-Grained Bimanual Task
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 18, 04:20 AM

  Nowadays, robotic telemanipulation enables humans to control robots so as to execute tasks in a manner similar to how they perform them, and serves as an essential approach for collecting on-robot data for robot learning by human demonstrations.

  Recently, semi-autonomous robotic telemanipulation has emerged as a promising direction that reduces operator workload while preserving human-in-the-loop control for task execution.

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