一个开源、可复现的能在障碍物间导航的张力整体机器人
An Open-Source, Reproducible Tensegrity Robot that can Navigate Among Obstacles
AI总结：
本文提出一个开源可复现的三杆张力整体机器人导航系统，集成硬件设计与建模、辨识、状态估计、规划和控制软件栈，并通过多种环境实验验证其鲁棒性与可复现性。
摘要：
张力整体机器人由刚性压杆和弹性绳索组成，具有抗冲击、质量轻以及适应非结构化地形的能力。然而，其柔顺性和复杂耦合动力学给建模与控制带来了挑战，阻碍了路径规划和避障。本文提出了一个完整、开源且可复现的系统，使三杆张力整体机器人能够实现导航。该系统包括：（i）一个低成本的开源硬件设计，以及（ii）一个集成的开源软件栈，用于基于物理的建模、系统辨识、状态估计、路径规划和控制。所有硬件和软件均可在 https://sites.google.com/view/tensegrity-navigation/ 公开获取。所提出的系统跟踪机器人的位姿，并在已知障碍物位置之间执行到指定目标的无碰撞路径。通过涉及未建模环境挑战的实验证明了系统的鲁棒性，这些挑战包括垂直跌落、斜坡和颗粒介质，最终进行了室外现场演示。为验证可复现性，在两个不同实验室使用机器人实例进行了实验。这项工作为机器人学界提供了一个适用于柔顺、抗冲击和可变形机器人的完整导航系统。该系统旨在作为推进其他非常规机器人平台导航能力的跳板。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
