开源可复现的张拉整体机器人实现障碍物间自主导航
An Open-Source, Reproducible Tensegrity Robot that can Navigate Among Obstacles
- 基于物理建模与状态估计,构建软体机器人完整导航系统
- 在垂直坠落、斜坡和颗粒介质中均能保持稳定导航
- 适合对柔性机器人和复杂环境导航感兴趣的科研人员
张拉整体机器人由刚性杆件和弹性缆索构成,具备抗冲击、质量轻、适应非结构化地形等优点。然而其柔顺性和复杂的耦合动力学给建模与控制带来挑战,制约路径规划与避障能力。本文提出一个完整的开源可复现系统,支持三杆张拉整体机器人的自主导航。系统包括:(i) 低成本开源硬件设计,(ii) 集成的开源软件栈,涵盖物理建模、系统辨识、状态估计、路径规划与控制。所有软硬件均公开于 https://sites.google.com/view/tensegrity-navigation/。该系统可追踪机器人位姿,并在已知障碍物环境中执行无碰撞路径至目标点。通过实验验证了系统鲁棒性,包含未建模环境挑战:垂直下落、斜坡、颗粒介质,最终完成户外实地演示。为验证可复现性,两不同实验室分别搭建机器人并成功复现实验。本工作为机器人社区提供了一个可拓展的柔性、抗冲击、可变形机器人导航平台,可作为其他非常规机器人平台导航发展的起点。
原文摘要 · Abstract (English)
Tensegrity robots, composed of rigid struts and elastic tendons, provide impact resistance, low mass, and adaptability to unstructured terrain. Their compliance and complex, coupled dynamics, however, present modeling and control challenges, hindering path planning and obstacle avoidance. This paper presents a complete, open-source, and reproducible system that enables navigation for a 3-bar tensegrity robot. The system comprises: (i) an inexpensive, open-source hardware design, and (ii) an integrated, open-source software stack for physics-based modeling, system identification, state estimation, path planning, and control. All hardware and software are publicly available at https://sites.google.com/view/tensegrity-navigation/. The proposed system tracks the robot's pose and executes collision-free paths to a specified goal among known obstacle locations. System robustness is demonstrated through experiments involving unmodeled environmental challenges, including a vertical drop, an incline, and granular media, culminating in an outdoor field demonstration. To validate reproducibility, experiments were conducted using robot instances at two different laboratories. This work provides the robotics community with a complete navigation system for a compliant, impact-resistant, and shape-morphing robot. This system is intended to serve as a springboard for advancing the navigation capabilities of other unconventional robotic platforms.
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