64 research outputs found
Motion Planning for Unlabeled Discs with Optimality Guarantees
We study the problem of path planning for unlabeled (indistinguishable)
unit-disc robots in a planar environment cluttered with polygonal obstacles. We
introduce an algorithm which minimizes the total path length, i.e., the sum of
lengths of the individual paths. Our algorithm is guaranteed to find a solution
if one exists, or report that none exists otherwise. It runs in time
, where is the number of robots and is the total
complexity of the workspace. Moreover, the total length of the returned
solution is at most , where OPT is the optimal solution cost. To
the best of our knowledge this is the first algorithm for the problem that has
such guarantees. The algorithm has been implemented in an exact manner and we
present experimental results that attest to its efficiency
Multi-agent Path Planning and Network Flow
This paper connects multi-agent path planning on graphs (roadmaps) to network
flow problems, showing that the former can be reduced to the latter, therefore
enabling the application of combinatorial network flow algorithms, as well as
general linear program techniques, to multi-agent path planning problems on
graphs. Exploiting this connection, we show that when the goals are permutation
invariant, the problem always has a feasible solution path set with a longest
finish time of no more than steps, in which is the number of
agents and is the number of vertices of the underlying graph. We then give
a complete algorithm that finds such a solution in time, with
being the number of edges of the graph. Taking a further step, we study time
and distance optimality of the feasible solutions, show that they have a
pairwise Pareto optimal structure, and again provide efficient algorithms for
optimizing two of these practical objectives.Comment: Corrected an inaccuracy on time optimal solution for average arrival
tim
Bearing-only formation control with auxiliary distance measurements, leaders, and collision avoidance
We address the controller synthesis problem for distributed formation control. Our solution requires only relative bearing measurements (as opposed to full translations), and is based on the exact gradient of a Lyapunov function with only global minimizers (independently from the formation topology). These properties allow a simple proof of global asymptotic convergence, and extensions for including distance measurements, leaders and collision avoidance. We validate our approach through simulations and comparison with other stateof-the-art algorithms.ARL grant W911NF-08-2-0004, ARO grant W911NF-13-1-0350, ONR grants N00014-07-1-0829, N00014-14-1-0510, N00014-15-1-2115, NSF grant IIS-1426840, CNS-1521617 and United Technologies
Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal with It
open5openD. Tateo, J. Banfi, A. Riva, F. Amigoni, A. BonariniTateo, Davide; Banfi, J.; Riva, Alessandro; Amigoni, F.; Bonarini, A
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