Stav Ashur
Papers
1
Total Citations
2
H-Index
1
About
Stav Ashur is a robotics researcher whose work focuses on advancing the foundations of robot motion planning, particularly through the lens of sampling-based algorithms. Her key research areas include motion planning, randomized algorithms, and heuristic-guided sampling strategies. Ashur’s major contribution lies in systematically evaluating guiding spaces for motion planning, as demonstrated in her most-cited paper, "Evaluating Guiding Spaces for Motion Planning" (2022, 2 citations). This work addresses the challenge of improving the efficiency of randomized sampling-based planners—widely used due to the intractability of motion planning—by moving beyond uniform random sampling. Instead, Ashur explores how biasing sampling with various heuristics can enhance algorithm performance across diverse problem instances. While her citation count is still growing, her research has practical implications for autonomous systems and robotics, offering a structured approach to understanding which guiding heuristics work best. Ashur’s work is notable for its experimental rigor and its potential to inform the design of more efficient motion planners, making her a promising voice in the field of algorithmic robotics.
Research Focus
Key Achievements
Top Papers
- 1Evaluating Guiding Spaces for Motion Planning2 citations · 2022