基于计算机视觉的路径规划与碰撞预防在小型多机器人试验台中的应用

Leandro Ponce, P. Cruz, D. Maldonado
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摘要

一个实际的测试平台对于缩小理论与实际应用之间的差距至关重要。路径规划和碰撞预防程序对于这些多机器人平台的可靠运行至关重要,因此可以提出,设计和测试越来越复杂的控制算法。本文介绍了基于ROS(机器人操作系统)的小型多机器人试验台的功能研究进展。一个高级路径规划器,一个碰撞预防程序和运动控制器被提出作为扩展到更复杂的应用程序,可以在测试平台上运行的一部分。设计了一种基于pid的姿态控制器和一种逆运动学位置控制器,并将其作为跟踪高级路径规划器生成的路点的可行方案进行了比较。软件模块化、可扩展性的改进和额外移动代理的增加也构成了这一新迭代测试平台的主要改进。给出并讨论了路径规划程序的结果,以及运动控制器的性能。
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Path Planning and Collision Prevention based on Computer Vision applied to a Mini-sized Multi-robot Testbed
A practical testbed is crucial to reduce the gap between theory and real-world applications. Path-planning and collision prevention routines are essential for a reliable operation of these multi-robot platforms, so increasingly complex control algorithms can be proposed, designed and tested. This paper describes the recent progress made on the functionality of a mini-sized multi-robot testbed that runs based on ROS (Robotic Operating System). A high-level path planner, a collision prevention routine and motion controllers are proposed as part of the expansion to more complex applications that can run on the testbed. A PID-based orientation controller and an Inverse Kinematics position controller are designed and compared as viable solutions for following the waypoints generated by the high-level path planner. Improvements on software modularity, scalability and the addition of an extra mobile agent also comprise the main improvements for this new iteration of the testbed. The results of the path-planning routine, as well as the performance of the motion controllers are presented and discussed.
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