Multi-Agent Planning with Spatio-Temporal and Topological Constraints using STL-

arXiv:2605.01222v1 Announce Type: new Abstract: Signal Temporal Logic (STL) offers verifiable task specifications and is crucial for safety-critical control. Yet STL planning

arXiv:2603.29868v1 Announce Type: new Abstract: The reliability of autonomous systems depends on their robustness, i.e., their ability to meet their objectives under uncertainty.

arXiv:2603.10651v2 Announce Type: replace-cross Abstract: Task and Motion Planning combines high-level task sequencing (what to do) with low-level motion planning (how to do it)

arXiv:2506.16931v2 Announce Type: replace Abstract: Effective and efficient task planning is essential for mobile robots, especially in applications like warehouse retrieval and

arXiv:2604.22748v1 Announce Type: new Abstract: As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment

arXiv:2605.00276v1 Announce Type: new Abstract: Trip planning for intelligent vehicles increasingly requires selecting optimal routes rather than merely producing feasible

arXiv:2604.05416v1 Announce Type: new Abstract: Multi-Agent Pathfinding (MAPF) plays a critical role in various domains. Traditional MAPF methods typically assume unit edge costs

arXiv:2606.15797v1 Announce Type: new Abstract: Compilation-based techniques represent an important stream of solvers for multi-agent path finding (MAPF) due to their modularity