Coordinated Motion Planning: Reconfiguring a Swarm of Labeled Robots with Bounded Stretch

01/05/2018
by   Erik D. Demaine, et al.
0

We present a number of breakthroughs for coordinated motion planning, in which the objective is to reconfigure a swarm of labeled convex objects by a combination of parallel, continuous, collision-free translations into a given target arrangement. Problems of this type can be traced back to the classic work of Schwartz and Sharir (1983), who gave a method for deciding the existence of a coordinated motion for a set of disks between obstacles; their approach is polynomial in the complexity of the obstacles, but exponential in the number of disks. Other previous work has largely focused on sequential schedules, in which one robot moves at a time. We provide constant-factor approximation algorithms for minimizing the execution time of a coordinated, parallel motion plan for a swarm of robots in the absence of obstacles, provided some amount of separability. Our algorithm achieves constant stretch factor: If all robots are at most d units from their respective starting positions, the total duration of the overall schedule is O(d). Extensions include unlabeled robots and different classes of robots. We also prove that finding a plan with minimal execution time is NP-hard, even for a grid arrangement without any stationary obstacles. On the other hand, we show that for densely packed disks that cannot be well separated, a stretch factor Ω(N^1/4) may be required. On the positive side, we establish a stretch factor of O(N^1/2) even in this case.

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