Echo Overview
Echo is an innovative teleoperation system designed to streamline the collection of high-quality datasets for training robots, particularly for manual and bimanual tasks. Built on a joint-matching strategy, it enables users to intuitively control a robot by mirroring its joint movements.
Key Features
- Force Feedback: Echo incorporates a force feedback mechanism that provides users with tactile sensations corresponding to the forces experienced by the robot, enhancing precision and intuitiveness during operation.
- Adjustable Sensitivity Modes: The system offers customizable sensitivity levels, allowing users to tailor control precision to suit tasks of varying complexity.
- User-Friendly Data Recording Interface: An integrated interface simplifies the process of recording datasets, making data collection for imitation learning fast and efficient.
Design and Accessibility
Echo is engineered for reliability, cost-effectiveness, and ease of reproduction. This makes it an accessible tool not only for well-funded research laboratories but also for startups and individual researchers passionate about advancing robotics through imitation learning.
Adaptability
While currently optimized for the UR (Universal Robots) manipulator, Echo’s modular architecture allows it to be reconfigured for use with other robotic platforms, including humanoid systems. This flexibility broadens its range of applications.
Proven Effectiveness
A series of experiments has demonstrated Echo’s ability to effectively perform complex bimanual tasks. These results highlight its potential to accelerate research in robotics by providing a reliable tool for data collection and the development of new algorithms.
Echo offers a powerful solution for those working to advance robotic systems, combining intuitive control, affordability, and adaptability. It stands as a valuable asset in the evolution of robot learning technologies.
Build Your Own Echo
If you are interested in building your own Echo, check out our Hardware & Assembly instructions.
BibTeX
@misc{bazhenov2025echoopensourcelowcostteleoperation,
title={Echo: An Open-Source, Low-Cost Teleoperation System with Force Feedback for Dataset Collection in Robot Learning},
author={Artem Bazhenov and Sergei Satsevich and Sergei Egorov and Farit Khabibullin and Dzmitry Tsetserukou},
year={2025},
eprint={2504.07939},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2504.07939},
}