运动规划
四轴飞行器
机器人
计算机科学
移动机器人
地形
能源消耗
路径(计算)
实时计算
高效能源利用
模拟
控制工程
工程类
人工智能
航空航天工程
电气工程
程序设计语言
生物
生态学
作者
Brandon Araki,John Strang,Sarah Pohorecky,Celine Qiu,Tobias Naegeli,Daniela Rus
标识
DOI:10.1109/icra.2017.7989657
摘要
The multi-robot path planning problem has been extensively studied for the cases of flying and driving vehicles. However, path planning for the case of vehicles that can both fly and drive has not yet been considered. Driving robots, while stable and energy efficient, are limited to mostly flat terrain. Quadcopters, on the other hand, are agile and highly mobile but have low energy efficiency and limited battery life. Combining a quadcopter with a driving mechanism presents a path planning challenge by enabling the selection of paths based off of both time and energy consumption. In this paper, we introduce a framework for multi-robot path planning for a swarm of flying-and-driving vehicles. By putting a lightweight driving platform on a quadcopter, we create a robust vehicle with an energy efficient driving mode and an agile flight mode. We extend two algorithms, priority planning with Safe Interval Path Planning and a multi-commodity network flow ILP, to accommodate multimodal locomotion, and we show that these algorithms can indeed plan collision-free paths for flying-and-driving vehicles on 3D graphs. Finally, we demonstrate that our system is able to plan paths and control the motions of 8 of our vehicles in a miniature town.
科研通智能强力驱动
Strongly Powered by AbleSci AI