Felix Wolff
Papers
1
Total Citations
23
H-Index
1
About
Felix Wolff is a leading researcher in robot manipulation and motion planning under uncertainty. His work fundamentally addresses how robots can robustly interact with the physical world by leveraging contact. Wolff’s key contributions lie in developing planning algorithms that strategically interleave free-space motion with deliberate contact, using the environment to reduce positional uncertainty. His highly cited 2017 paper, "Interleaving motion in contact and in free space for planning under uncertainty," introduced a planner that grows a search tree through both collision-free and contact configurations, efficiently reasoning about accumulated uncertainty. This work, garnering 23 citations, is foundational for tasks like assembly and peg-in-hole insertion, where precision is critical. Wolff's research bridges the gap between theoretical planning and practical robotic dexterity, demonstrating how uncertainty can be actively managed rather than simply avoided. His insights are essential for advancing robots from controlled labs to unstructured, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1