Echo: 力覚フィードバック付きのオープンソース低コスト遠隔操作システムによるロボット学習用データセット収集
Echo: An Open-Source, Low-Cost Teleoperation System with Force Feedback for Dataset Collection in Robot Learning
力覚フィードバックと感度調整機能を備えた低コストな遠隔操作システムEchoを開発し、URマニピュレータでの両手タスクの模倣学習用データ収集を容易にした。
著者: Artem Bazhenov, Sergei Satsevich, Sergei Egorov, Farit Khabibullin, Dzmitry Tsetserukou
分類: cs.RO
原文アブストラクト
In this article, we propose Echo, a novel joint-matching teleoperation system designed to enhance the collection of datasets for manual and bimanual tasks. Our system is specifically tailored for controlling the UR manipulator and features a custom controller with force feedback and adjustable sensitivity modes, enabling precise and intuitive operation. Additionally, Echo integrates a user-friendly dataset recording interface, simplifying the process of collecting high-quality training data for imitation learning. The system is designed to be reliable, cost-effective, and easily reproducible, making it an accessible tool for researchers, laboratories, and startups passionate about advancing robotics through imitation learning. Although the current implementation focuses on the UR manipulator, Echo architecture is reconfigurable and can be adapted to other manipulators and humanoid systems. We demonstrate the effectiveness of Echo through a series of experiments, showcasing its ability to perform complex bimanual tasks and its potential to accelerate research in the field. We provide assembly instructions, a hardware description, and code at https://eterwait.github.io/Echo/.
