Towards autonomously traversing complex obstacles with mobile robots with adjustable chassis

M. Brunner, B. Bruggemann, D. Schulz
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引用次数: 13

Abstract

Looking at the mobility of robots and their chassis most are limited to fairly flat environments. In urban environments common structures such as steps or stairs pose invincible obstacles for such systems. When it comes to unstructured outdoor environments a vast variety of obstacles is imaginable which are not traversable by common robots, for instance boulders, debris, rocks or trunks of fallen or chopped trees. However, there are mobile robots with adjustable chassis providing a higher degree of mobility and enabling them to overcome such obstacles. This paper presents first results on our motion planning algorithm which aims at utilizing the enhanced capabilities of those robots. It takes into account the chassis configuration and the system stability to propose the best path. We use a high level planner to quickly generate a preliminary path by considering the platform's operating limits. We then distinguish between path segments on flat and rough terrain. For each hard segment we restrict the search space to a tube around the initial path. A subsequent planner is used to refine the preliminary path by considering the actuator positions, the robot's stability and a ground contact factor. Our planning algorithm is general in the sense that we do not categorize obstacles and do not use predefined motion sequences for those obstacle classes. Finally, we present a discussion including an analysis of the time complexity and a simulation application in ROS and Gazebo as proof of feasability.
可调底盘移动机器人自主穿越复杂障碍物的研究
看看机器人的机动性和它们的底盘,大多数都局限于相当平坦的环境。在城市环境中,台阶或楼梯等常见结构对此类系统构成了不可逾越的障碍。当涉及到非结构化的户外环境时,可以想象到各种各样的障碍,这些障碍是普通机器人无法穿越的,例如巨石、碎片、岩石或倒下或砍断的树干。然而,有一些可调节底盘的移动机器人提供了更高程度的机动性,使它们能够克服这些障碍。本文介绍了我们的运动规划算法的初步结果,该算法旨在利用这些机器人的增强功能。它考虑了机箱的配置和系统的稳定性,提出了最优路径。通过考虑平台的运行限制,我们使用高级规划器快速生成初步路径。然后,我们区分平坦地形和崎岖地形上的路径段。对于每个硬段,我们将搜索空间限制在初始路径周围的一个管道中。通过考虑致动器位置、机器人稳定性和地面接触系数,利用后续规划器优化初始路径。我们的规划算法是通用的,因为我们不对障碍进行分类,也不为这些障碍类别使用预定义的运动序列。最后,我们进行了讨论,包括对时间复杂度的分析以及在ROS和Gazebo中的仿真应用,以证明该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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