An Integral Framework of Task Assignment and Path Planning for Multiple Unmanned Aerial Vehicles in Dynamic Environments
An Integral Framework of Task Assignment and Path Planning for Multiple Unmanned Aerial Vehicles in Dynamic Environments
复制标题
DOI：
10.1007/s10846-012-9740-3
复制
发表时间：
2013-04-01
影响因子：
3.3
通讯作者：
Shim, David Hyunchul
中科院分区：
文献类型：
--
作者：
Moon, Sangwoo;Oh, Eunmi;Shim, David Hyunchul
提出了一种动态环境下多无人机任务分配和路径规划的层次化框架。对于动态环境中的多智能体场景，候选算法应该能够重新规划新的路径来执行更新的任务，而不会在使命期间与障碍物或其他智能体发生任何碰撞。在本文中，我们提出了一个基于交集的路径生成算法和一个基于协商的任务分配算法，因为这些算法能够以较小的计算成本生成可接受的路径。路径规划算法还增加了一个潜在的基于场的轨迹重规划器，解决了绕其他代理或弹出障碍物的绕行轨迹。为了验证，多无人机在动态环境中执行合作任务的测试方案被认为是。在室外环境下的固定翼无人机试验平台上实现了所提出的算法，并在存在静态和弹出式障碍物以及其他智能体的情况下表现出令人满意的性能，以完成使命。
In this paper, a hierarchical framework for task assignment and path planning of multiple unmanned aerial vehicles (UAVs) in a dynamic environment is presented. For multi-agent scenarios in dynamic environments, a candidate algorithm should be able to replan for a new path to perform the updated tasks without any collision with obstacles or other agents during the mission. In this paper, we propose an intersection-based algorithm for path generation and a negotiation-based algorithm for task assignment since these algorithms are able to generate admissible paths at a smaller computing cost. The path planning algorithm is also augmented with a potential field-based trajectory replanner, which solves for a detouring trajectory around other agents or pop-up obstacles. For validation, test scenarios for multiple UAVs to perform cooperative missions in dynamic environments are considered. The proposed algorithms are implemented on a fixed-wing UAVs testbed in outdoor environment and showed satisfactory performance to accomplish the mission in the presence of static and pop-up obstacles and other agents.