Alexandre Amice
Papers
5
Total Citations
55
H-Index
4
About
Alexandre Amice is a rising star in robotics, whose research focuses on bridging the gap between rigorous geometric reasoning and practical motion planning. His core contributions lie in developing certifiable algorithms for robot manipulation, particularly by representing complex, collision-free configuration spaces as collections of simple convex sets. His most influential work, "Finding and Optimizing Certified, Collision-Free Regions in Configuration Space for Robot Manipulators" (2022, 20 citations), introduced a method to compute provably safe regions, enabling the use of fast convex optimization for trajectory design. Building on this, his 2024 paper on using clique covers of visibility graphs (13 citations) dramatically accelerates these computations, while his work on "Tight Convex Relaxations for Contact-Rich Manipulation" (11 citations) tackles the hybrid nature of tasks involving physical interaction. Amice has also demonstrated the power of sums-of-squares optimization for synthesizing certifiable controllers for nonlinear systems like quadrotors. By providing rigorous, optimization-based frameworks, his work is paving the way for robots that can plan and execute complex, contact-rich tasks with formal guarantees of safety and performance.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Towards Tight Convex Relaxations for Contact-Rich Manipulation11 citations · 2024
- 4
- 5