{"type":"ScholarlyArticle","title":"Switched Linear Multi-Robot Navigation Using Hierarchical Model Predictive Control","authors":[{"name":"Chao Huang","slug":"chao-huang","given":"Chao","family":"Huang","affiliation":"State Key Laboratory for Novel Software Technology , Nanjing University , Nanjing , China"},{"name":"Xin Chen","slug":"xin-chen","given":"Xin","family":"Chen","affiliation":"State Key Laboratory for Novel Software Technology , Nanjing University , Nanjing , China"},{"name":"Yifan Zhang","slug":"yifan-zhang","given":"Yifan","family":"Zhang","affiliation":"State Key Laboratory for Novel Software Technology , Nanjing University , Nanjing , China"},{"name":"Shengchao Qin","slug":"shengchao-qin","given":"Shengchao","family":"Qin","affiliation":"Shenzhen University , Shenzhen , China"},{"name":"Yifeng Zeng","slug":"yifeng-zeng","given":"Yifeng","family":"Zeng","affiliation":"School of Computing , Teesside University , Tees Valley , TS1 3BX , UK"},{"name":"Xuandong Li","slug":"xuandong-li","given":"Xuandong","family":"Li","affiliation":"State Key Laboratory for Novel Software Technology , Nanjing University , Nanjing , China"}],"abstract":"Multi-robot navigation control in the absence of reference trajectory is rather challenging as it is expected to ensure stability and feasibility while still offer fast computation on control decisions. The intrinsic high complexity of switched linear dynamical robots makes the problem even more challenging. In this paper, we propose a novel HMPC based method to address the navigation problem of multiple robots with switched linear dynamics. We develop a new technique to compute the reachable sets of switched linear systems and use them to enable the parallel computation of control parameters. We present theoretical results on stability, feasibility and complexity of the proposed approach, and demonstrate its empirical advance in performance against other approaches.","doi":"10.24963/ijcai.2017/605","url":"https://ijcai.org/proceedings/2017/605","pdf":"https://ijcai.org/proceedings/2017/0605.pdf","markdown":"https://ijcai.org/proceedings/2017/605.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/605","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Planning and Scheduling","track":"Main track","number":605,"pages":{"first":4331,"last":4337},"keywords":["Robotics and Vision: Multi-Robot Systems","Robotics and Vision: Motion and Path Planning","Planning and Scheduling: Distributed/Multi-agent Planning"],"videos":[],"references":[{"position":1,"raw":"[Alur et al., 1995] Rajeev Alur, Costas Courcoubetis, Nico- las Halbwachs, Thomas A Henzinger, P-H Ho, Xavier Nicollin, Alfredo Olivero, Joseph Sifakis, and Sergio Yovine. 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