Exploiting subgraph structure in multi-robot path planning
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In this article, the map is partitioned into subgraphs of known structure with entry and exit restrictions and planning then becomes a search in the much smaller space of subgraph configurations.Abstract:
Multi-robot path planning is dificult due to the combinatorial explosion of the search space with every new robot added Complete search of the combined state-space soon becomes intractable In this paper we present a novel form of abstraction that allows us to plan much more eficiently The key to this abstraction is the partitioning of the map into subgraphs of known structure with entry and exit restrictions which we can represent compactly Planning then becomes a search in the much smaller space of subgraph configurations Once an abstract plan is found, it can be quickly resolved into a correct (but possibly sub-optimal) concrete plan without the need for further search We prove that this technique is sound and complete and demonstrate its practical effiectiveness on a real map
A contending solution, prioritised planning, is also evaluated and shown to have similar performance albeit at the cost of completeness The two approaches are not necessarily conflicting; we demonstrate how they can be combined into a single algorithm which out-performs either approach aloneread more
Citations
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Conflict-based search for optimal multi-agent path finding
TL;DR: In this article, a two-level algorithm called Conflict Based Search (CBS) is proposed to solve the multi-agent path finding problem, where at the high level, a search is performed on a tree based on conflicts between agents.
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Conflict-based search for optimal multi-agent pathfinding
TL;DR: A new search algorithm called Conflict Based Search (CBS), which enables CBS to examine fewer states than A* while still maintaining optimality and shows a speedup of up to a full order of magnitude over previous approaches.
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Efficient informative sensing using multiple robots
TL;DR: ESIP (efficient Single-robot Informative Path planning), an approximation algorithm for optimizing the path of a single robot, and a general technique, sequential allocation, which can be used to extend any single robot planning algorithm, such as eSIP, for the multi-ro robot problem.
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Finding optimal solutions to cooperative pathfinding problems
TL;DR: This work proposes a technique called operator decomposition, which can be used to reduce the branching factors of many search algorithms, including algorithms for cooperative pathfinding, and shows how a type of independence common in instances of Cooperative pathfinding problems can be exploited.
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Structure and intractability of optimal multi-robot path planning on graphs
Jingjin Yu,Steven M. LaValle +1 more
TL;DR: The NP-hardness proof for the time optimal versions of the discrete multi-robot path planning problem shows that these problems remain NP- hard even when there are only two groups of robots (i.e. robots within each group are interchangeable).
References
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MonographDOI
Planning Algorithms: Introductory Material
TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
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Planning in a hierarchy of abstraction spaces
TL;DR: Examples of the ABSTRIPS system's performance are presented that demonstrate the significant increases in problem-solving power that this approach provides, and some further implications of the hierarchical planning approach are explored.
Journal ArticleDOI
Robot motion planning: a distributed representation approach
TL;DR: A new approach to robot path planning that consists of building and searching a graph connecting the local minima of a potential function defined over the robot's configuration space is proposed and a planner based on this approach has been implemented.
Journal ArticleDOI
On multiple moving objects
TL;DR: This paper explores the motion-planning problem for multiple moving objects by assigning priorities to the objects, then planning motions one object at a time, using two-dimensional slices.