activity
20122017
most citedMotion Planning for Unlabeled Discs with Optimality Guarantees

23 citations · 24 across the 3 of their papers we have counts for

collaborators

6 papers

cs.MA2017

Scalable Asymptotically-Optimal Multi-Robot Motion Planning

Andrew Dobson, Kiril Solovey, Rahul Shome +2

Finding asymptotically-optimal paths in multi-robot motion planning problems could be achieved, in principle, using sampling-based planners in the composite configuration space of…

cs.RO2017

Effective Metrics for Multi-Robot Motion-Planning

Aviel Atias, Kiril Solovey, Oren Salzman +1

We study the effectiveness of metrics for Multi-Robot Motion-Planning (MRMP) when using RRT-style sampling-based planners. These metrics play the crucial role of determining the ne…

cs.CG20161 cited

Sampling-based bottleneck pathfinding with applications to Frechet matching

Kiril Solovey, Dan Halperin

We describe a general probabilistic framework to address a variety of Frechet-distance optimization problems. Specifically, we are interested in finding minimal bottleneck-paths in…

cs.RO2016

New perspective on sampling-based motion planning via random geometric graphs

Kiril Solovey, Oren Salzman, Dan Halperin

Roadmaps constructed by many sampling-based motion planners coincide, in the absence of obstacles, with standard models of random geometric graphs (RGGs). Those models have been st…

cs.CG201523 cited

Motion Planning for Unlabeled Discs with Optimality Guarantees

Kiril Solovey, Jingjin Yu, Or Zamir +1

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…

cs.RO2012

Sparsification of Motion-Planning Roadmaps by Edge Contraction

Doron Shaharabani, Oren Salzman, Pankaj K. Agarwal +1

We present Roadmap Sparsification by Edge Contraction (RSEC), a simple and effective algorithm for reducing the size of a motion-planning roadmap. The algorithm exhibits minimal ef…