arXiv:2603. 23405v2 Announce Type: replace-cross Abstract: Modern Multi-Agent Path Finding (MAPF) algorithms must plan for hundreds to thousands of agents in congested environments within a second, requiring highly efficient algorithms.
By Zixiang Jiang, Yulun Zhang, Rishi Veerapaneni, Jiaoyang Li
arXiv:2607. 00444v1 Announce Type: cross Abstract: Spatiotemporal motion planning, especially in multi-robot settings, requires robots to reason about collision-free regions that change over time, which is challenging in continuous spaces when feasible regions are transient and geometrically constrained.
By Jingtao Tang, Zining Mao, Lufan Yang, Hang Ma
arXiv:2406. 09953v4 Announce Type: replace-cross Abstract: Dual-arm robots promise greater efficiency but require planning for complex tasks with nonlinear sub-task dependencies.
By Zeyu Gao, Yao Mu, Jinye Qu, Mengkang Hu, Shijia Peng, Chengkai Hou, Lingyue Guo, Ping Luo, Shanghang Zhang, Yanfeng Lu
arXiv:2609.39559v1 Announce Type: new
Abstract: In this work we study the problem of MAPFC, a post-optimization step for Multi-Agent Path Finding (MAPF) plans where we are given a feasible plan produ...
By Oren Salzman
arXiv:2512.00939v3 Announce Type: replace-cross
Abstract: Recent progress in contact-rich robotic manipulation has been striking, yet most deployed systems remain confined to simple, scripted routine...
By Nayesha Gandotra, Itamar Mishani, Lai Yuan, Oren Salzman, Maxim Likhachev
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