{"type":"ScholarlyArticle","title":"From Gridworlds to Warehouses: Adapting Lightweight One-shot Multi-Agent Pathfinding for AGVs","authors":[{"name":"Hiroki Nagai","slug":"hiroki-nagai","given":"Hiroki","family":"Nagai","affiliation":""},{"name":"Keisuke Okumura","slug":"keisuke-okumura","given":"Keisuke","family":"Okumura","affiliation":""}],"abstract":"Multi-agent pathfinding (MAPF) under one-shot planning is a core component of warehouse automation, yet classical formulations typically assume four-connected 2D grids with unit-time moves in four directions. To fill reality gaps while still being trackable with discrete combinatorial search, this work proposes a more practical counterpart tailored to differential-drive AGVs. We term this multi-agent warehouse pathfinding (MAWPF), featured with four constraints: (i) agent actions are restricted to straight motion and in-place rotation; (ii) rotations require multi-step costs; (iii) acceleration and deceleration are considered, and; (iv) follower collisions are prohibited to prevent rear-end crashes. To solve MAWPF efficiently, we adapt representative suboptimal MAPF algorithms-PP, LNS2, PIBT, and LaCAM-and conduct comprehensive benchmarking. Our experiments reveal that PP and LNS2 struggle to solve instances with many agents, while PIBT-based approaches achieve preferable scalability with increased solution cost. We believe that these constitute an important step toward adapting classical gridworld MAPF to operational warehouse setups.","doi":"10.24963/ijcai.2026/35","url":"https://ijcai.org/proceedings/2026/35","pdf":"https://ijcai.org/proceedings/2026/0035.pdf","markdown":"https://ijcai.org/proceedings/2026/35.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/35","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":35,"pages":{"first":306,"last":313},"keywords":["Agent-based and Multi-agent Systems: Multi-agent planning","Search: Heuristic search","Robotics: Motion and path planning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}