AI 中文总结
针对竞争环境中UAS机群路线规划问题，提出整合稳健性和恢复力组件的策略，包括航路点位置重叠和动态任务适配，提升任务成功率，为UAS任务规划提供新方向。
AI 中文摘要
无人自主系统（UAS）能在大范围区域进行远程目标感知，但在竞争环境中易受威胁。当前方法通过UAS路径规划考虑效率，然而优先考虑稳健性（即承受干扰的能力）和恢复力（即从干扰中恢复的能力）的任务虽能提高任务成功率却很少被考虑。本文针对异构威胁环境中的UAS机群提出稳健且有恢复力的路线规划策略。通过在路线规划中整合稳健性和恢复力组件，允许UAS在航路点位置重叠及进行动态任务适配，可提高完全区域覆盖任务的成功率。结果表明，专注稳健性的策略在任务成功率上比基于效率的策略有显著提升，基于恢复力的策略优于基于效率和稳健性的策略。所提出的方法为将稳健性和恢复力明确纳入UAS任务规划提供了有前景的未来研究方向。
英文摘要
Unmanned Autonomous Systems (UASs) can remotely sense targets across large-scale areas but may be vulnerable to threats in contested environments. Current approaches consider efficiency through UAS path planning, but missions prioritizing robustness (i.e., the capacity to withstand disruptions) and resilience (i.e., the ability to recover from disruptions) are rarely considered despite their ability to increase mission success. This paper presents robust and resilient strategies for route planning for a fleet of UASs in a heterogeneous threat landscape. By integrating components of robustness and resilience in route planning through allowing the UASs to overlap in the waypoint locations and dynamic mission adaptation, the probability of mission success of complete area coverage can be increased. The results show that a robustness-focused strategy shows significant improvement in probability of mission success over an efficiency-based strategy, and that a resilience-based strategy outperforms both the efficiency- and robustness- based strategies. The specified methodologies provide promising future directions of research to explicitly incorporate robustness and resilience into UAS mission planning.
