21 citations · 33 across the 8 of their papers we have counts for
9 papers
Manifold-Guided Motion Planning for Tight Assemblies
Dror Livnat, Michael M. Bilevich, Michal Kleinbort +1
Motion planning for rigid-body assembly poses a fundamental challenge in robotics due to tight geometric constraints. In such scenarios, feasible motions often require passing thro…
Evaluating Large Language Models on Computer Science University Exams in Data Structures
Edan Gabay, Yael Maoz, Jonathan Stahl +7
We present a comprehensive evaluation of Large Language Models (LLMs) on Computer Science (CS) Data Structure examination questions. Our work introduces a new benchmark dataset com…
Refined Analysis of Asymptotically-Optimal Kinodynamic Planning in the State-Cost Space
Michal Kleinbort, Edgar Granados, Kiril Solovey +3
We present a novel analysis of AO-RRT: a tree-based planner for motion planning with kinodynamic constraints, originally described by Hauser and Zhou (AO-X, 2016). AO-RRT explores…
Probabilistic completeness of RRT for geometric and kinodynamic planning with forward propagation
Michal Kleinbort, Kiril Solovey, Zakary Littlefield +2
The Rapidly-exploring Random Tree (RRT) algorithm has been one of the most prevalent and popular motion-planning techniques for two decades now. Surprisingly, in spite of its centr…
The Critical Radius in Sampling-based Motion Planning
Kiril Solovey, Michal Kleinbort
We develop a new analysis of sampling-based motion planning in Euclidean space with uniform random sampling, which significantly improves upon the celebrated result of Karaman and…
Collision detection or nearest-neighbor search? On the computational bottleneck in sampling-based motion planning
Michal Kleinbort, Oren Salzman, Dan Halperin
The complexity of nearest-neighbor search dominates the asymptotic running time of many sampling-based motion-planning algorithms. However, collision detection is often considered…
Optimal randomized incremental construction for guaranteed logarithmic planar point location
Michael Hemmer, Michal Kleinbort, Dan Halperin
Given a planar map of segments in which we wish to efficiently locate points, we present the first randomized incremental construction of the well-known trapezoidal-map search-…
Efficient high-quality motion planning by fast all-pairs r-nearest-neighbors
Michal Kleinbort, Oren Salzman, Dan Halperin
Sampling-based motion-planning algorithms typically rely on nearest-neighbor (NN) queries when constructing a roadmap. Recent results suggest that in various settings NN queries ma…
Improved Implementation of Point Location in General Two-Dimensional Subdivisions
Michael Hemmer, Michal Kleinbort, Dan Halperin
We present a major revamp of the point-location data structure for general two-dimensional subdivisions via randomized incremental construction, implemented in CGAL, the Computatio…