TelePreview: A User-Friendly Teleoperation System with Virtual Arm Assistance for Enhanced Effectiveness

2024-12-18

AI Summary

Novice operators face significant challenges in teleoperating robots, including high operational complexity, poor safety guarantees, and limited cross-platform compatibility—factors that hinder both robot learning and efficient data collection. To address these issues, we propose a low-cost (<$1,000) teleoperation system featuring a novel real-time virtual arm visualization mechanism that enables pre-execution rehearsal of commands, supporting seamless toggling between action preview and execution. The system leverages lightweight motion mapping, real-time virtual rendering, and low-latency interactive feedback, requiring no specialized hardware and ensuring compatibility with mainstream robotic arm platforms. Evaluated on five dexterous manipulation tasks, our approach outperforms existing methods in task success rate and operator efficiency. It substantially reduces the learning curve for novice users and improves operational safety. All source code and deployment documentation are publicly released under an open-source license.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Low Level & Physics-based Vision
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Teleoperation provides an effective way to collect robot data, which is crucial for learning from demonstrations. In this field, teleoperation faces several key challenges: user-friendliness for new users, safety assurance, and transferability across different platforms. While collecting real robot dexterous manipulation data by teleoperation to train robots has shown impressive results on diverse tasks, due to the morphological differences between human and robot hands, it is not only hard for new users to understand the action mapping but also raises potential safety concerns during operation. To address these limitations, we introduce TelePreview. This teleoperation system offers real-time visual feedback on robot actions based on human user inputs, with a total hardware cost of less than $1,000. TelePreview allows the user to see a virtual robot that represents the outcome of the user's next movement. By enabling flexible switching between command visualization and actual execution, this system helps new users learn how to demonstrate quickly and safely. We demonstrate that it outperforms other teleoperation systems across five tasks, emphasize its ease of use, and highlight its straightforward deployment across diverse robotic platforms. We release our code and a deployment document on our website https://nus-lins-lab.github.io/telepreview/.

Problem

• Robot Teleoperation
• Learning Efficiency
• Operational Difficulty

Innovation

• TelePreview
• Real-time Preview
• Cross-platform Compatibility