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Search-based configuration planning and motion control algorithms for a snake-like robot performing load-intensive operations
Autonomous Robots ( IF 3.5 ) Pub Date : 2021-09-24 , DOI: 10.1007/s10514-021-10017-6
Xiaolong Wang 1 , Subhrajit Bhattacharya 1 , Matthew Bilsky 2
Affiliation  

Snake-like robots can enable workers to avoid difficult-to-reach, dangerous, and hazardous environments while enhancing their capabilities. The technologies developed for a snake-like robot can be transferred to applications such as robotic exploration, minimally invasive surgical robotics, and robotic manipulation in manufacturing industries. In this paper we consider high-load tasks, such as drilling through the studs inside a wall, using a snake-like robot. The key technical innovation in this work is to design a search-based planning algorithm for high degree of freedom articulated systems that explicitly takes into account contact with surfaces in the environment in order to garner mechanical support for performing load-intensive tasks. In case of a snake-like robot, contacts with the studs and other structural members within walls need to be exploited to its advantage for bracing against walls for support in order to climb up or perform load-intensive operations such as drilling. We present a contact-augmented graph construction, which is the main technical tool for finding stable load-bearing configurations. We also develop motion controllers for moving the robot into the planned configuration and progressing the robot during the drilling process. We validate the algorithms through simulation and introduce a preliminary experimental setup.



中文翻译:

用于执行负载密集型操作的蛇形机器人的基于搜索的配置规划和运动控制算法

蛇形机器人可以让工人在提升能力的同时,避开难以触及的、危险的和危险的环境。为蛇形机器人开发的技术可以转移到机器人探索、微创手术机器人和制造行业的机器人操作等应用中。在本文中,我们考虑了高负载任务,例如使用蛇形机器人钻穿​​墙内的螺柱。这项工作的关键技术创新是为高自由度铰接系统设计一种基于搜索的规划算法,该算法明确考虑与环境中的表面接触,以便为执行负载密集型任务获得机械支持。如果是蛇形机器人,需要充分利用与墙内立柱和其他结构构件的接触,以支撑墙壁以提供支撑,以便爬上或执行诸如钻孔之类的负载密集型操作。我们提出一个接触增强图构建,这是寻找稳定承载配置的主要技术工具。我们还开发了运动控制器,用于将机器人移动到计划配置并在钻孔过程中推进机器人。我们通过模拟验证算法并介绍初步实验设置。

更新日期:2021-09-28
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