Multi-Agent Path Finding on Real Robots

Multi-agent path finding (MAPF) deals with the problem of finding a collision-free path for a set of agents in a graph. It is an abstract version of the problem to coordinate movement for a set of mobile robots. This demo presents software guiding through the MAPF task, starting from the problem formulation and finishing with execution of plans on real robots. Users can design grid-like maps, specify initial and goal locations of robots, generate plans using various abstract models implemented in the Picat programming language, simulate and visualize execution of these plans, and translate the plans to command sequences for Ozobots, small robots developed for teaching programming.

[1]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[2]  Adi Botea,et al.  Fast and Memory-Efficient Multi-Agent Pathfinding , 2008, ICAPS.

[3]  Pavel Surynek,et al.  An Optimization Variant of Multi-Robot Path Planning Is Intractable , 2010, AAAI.

[4]  David Silver,et al.  Cooperative Pathfinding , 2005, AIIDE.

[5]  Malcolm Ross Kinsella Ryan.  Exploiting Subgraph Structure in Multi-Robot Path Planning , 2008, J. Artif. Intell. Res..

[6]  Roman Barták,et al.  Modeling and Solving the Multi-agent Pathfinding Problem in Picat , 2017, 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI).

[7]  Steven M. LaValle,et al.  Structure and Intractability of Optimal Multi-Robot Path Planning on Graphs , 2013, AAAI.

[8]  Roman Barták,et al.  Multi-agent Path Finding on Real Robots: First Experience with Ozobots , 2018, IBERAMIA.

[9]  Pavel Surynek.  On Propositional Encodings of Cooperative Path-Finding , 2012, 2012 IEEE 24th International Conference on Tools with Artificial Intelligence.

[10]  Trevor Scott Standley.  Finding Optimal Solutions to Cooperative Pathfinding Problems , 2010, AAAI.

[11]  Bart Selman,et al.  Planning as Satisfiability , 1992, ECAI.

[12]  Steven M. LaValle,et al.  Planning optimal paths for multiple robots on graphs , 2012, 2013 IEEE International Conference on Robotics and Automation.

[13]  Paul G. Spirakis,et al.  Coordinating Pebble Motion on Graphs, the Diameter of Permutation Groups, and Applications , 2015, FOCS.

[14]  Pavel Surynek,et al.  Compact Representations of Cooperative Path-Finding as SAT Based on Matchings in Bipartite Graphs , 2014, 2014 IEEE 26th International Conference on Tools with Artificial Intelligence.

[15]  Peter Schüller,et al.  A General Formal Framework for Pathfinding Problems with Multiple Agents , 2013, AAAI.

[16]  Katsutoshi Hirayama,et al.  Collision Avoidance in Multiple-Ship Situations by Distributed Local Search , 2014, J. Adv. Comput. Intell. Intell. Informatics.

[17]  Vijay Kumar,et al.  Cooperative manipulation and transportation with aerial robots , 2009, Auton. Robots.

[18]  Roni Stern,et al.  The increasing cost tree search for optimal multi-agent pathfinding , 2011, Artif. Intell..

[19]  Roni Stern,et al.  The Increasing Cost Tree Search for Optimal Multi-Agent Pathfinding , 2011, IJCAI.

[20]  Manfred K. Warmuth,et al.  NxN Puzzle and Related Relocation Problem , 1990, J. Symb. Comput..

[21]  Nathan R. Sturtevant,et al.  Conflict-based search for optimal multi-agent pathfinding , 2012, Artif. Intell..

[22]  Roman Barták,et al.  k-Robust Multi-Agent Path Finding , 2017, SOCS.

[23]  Richard E. Korf,et al.  Complete Algorithms for Cooperative Pathfinding Problems , 2011, IJCAI.

[24]  Dinesh Manocha,et al.  Centralized path planning for multiple robots: Optimal decoupling into sequential plans , 2009, Robotics: Science and Systems.

[25]  Roman Barták,et al.  A Scheduling-Based Approach to Multi-Agent Path Finding with Weighted and Capacitated Arcs , 2018, AAMAS.

[26]  David Tolpin,et al.  ICBS: The Improved Conflict-Based Search Algorithm for Multi-Agent Pathfinding , 2015, SOCS.