Michael Kneebone
Papers
1
Total Citations
10
H-Index
1
About
Michael Kneebone is a researcher in robotics and motion planning, with a focus on decision-making under uncertainty. His most-cited work, “Navigation Planning in Probabilistic Roadmaps with Uncertainty” (2009, 10 citations), addresses a critical gap in robot navigation: how to plan safe paths when obstacle positions are imprecisely known. Kneebone extends the classic Probabilistic Roadmap (PRM) algorithm by analyzing edges that may intersect uncertain obstacles, offering a principled approach to risk-aware path selection. This contribution is foundational for autonomous systems operating in real-world, dynamic environments where perfect sensing is impossible. While his citation count reflects a specialized niche, Kneebone’s work has influenced subsequent research on robust motion planning and probabilistic collision checking. His approach bridges theoretical rigor with practical robotics challenges, making him a notable figure in the subfield of navigation under uncertainty. For students and researchers, Kneebone’s work exemplifies how addressing real-world constraints—like imperfect information—can advance core algorithms in robotics.
Research Focus
Key Achievements
Top Papers
- 1Navigation Planning in Probabilistic Roadmaps with Uncertainty10 citations · 2009