arXiv:2607. 28679v1 Announce Type: new Abstract: Multi-agent planning problems arise in a variety of engineering applications, such as multi-robot wildfire fighting and unmanned aerial inspection in factories.
By Sheryl Paul, Vidisha Kudalkar, Anand Balakrishnan, Lars Lindemann, Alberto Speranzon, Jyotirmoy V. Deshmukh
arXiv:2607. 04124v1 Announce Type: cross Abstract: Employing multiple manipulators can boost efficiency and accomplish tasks that a single manipulator cannot do.
By Dongliang Zheng, Zhipeng Wang, Siqi Wang, Yuxi Lu, Bin He, Hesheng Wang, Panagiotis Tsiotras
arXiv:2608. 06702v1 Announce Type: cross Abstract: Lifelong Multi-Agent Path Finding (LMAPF) requires generating collision-free paths for large agent fleets under strict real-time constraints.
By Vaibhav Sanjay, Jiaoyang Li
arXiv:2607. 19306v1 Announce Type: cross Abstract: Autonomous flight in cluttered environments requires a robot to build a geometric map of its surroundings and plan safe, dynamically feasible trajectories, all onboard and in real time.
By Jason Stanley (UC San Diego, La Jolla, USA), Zhirui Dai (UC San Diego, La Jolla, USA), Qihao Qian (UC San Diego, La Jolla, USA), Tzu-Chin Ho (UC San Diego, La Jolla, USA), Tianxing Fan (UC San Diego, La Jolla, USA), Siddharth Saha (Shield AI, San Diego, USA), Christopher Barngrover (Shield AI, San Diego, USA), Ki Myung Brian Lee (UC San Diego, La Jolla, USA), Nikolay Atanasov (UC San Diego, La Jolla, USA)
arXiv:2604. 12474v3 Announce Type: replace-cross Abstract: In many robotic tasks, agents must traverse a sequence of spatial regions to complete a mission.
By Lidor Erez, Shahaf S. Shperberg, Ayal Taitler
arXiv:2608. 05588v1 Announce Type: cross Abstract: Lifelong Multi-Agent Path Finding (LMAPF) requires repeatedly planning collision-free paths for agents that continuously receive new goals upon reaching their current ones.
By He Jiang, Jingtian Yan, Yulun Zhang, Yimin Tang, Tanishq Duhan, Rishi Veerapaneni, Guillaume Sartoretti, Jiaoyang Li