Jean-Pierre Sleiman

ETH Zurich

Papers

7

Total Citations

199

H-Index

5

About

Jean-Pierre Sleiman is at the forefront of legged mobile manipulation, pioneering real-time planning and control frameworks that enable robots to dynamically coordinate locomotion with manipulation. His most impactful work, a collision-free Model Predictive Control (MPC) approach for whole-body dynamic locomotion and manipulation (69 citations), introduces a real-time planner that enforces self- and environment-collision avoidance as soft constraints within a multi-contact optimal control problem. This breakthrough allows legged robots to safely navigate cluttered spaces while manipulating objects. Sleiman’s versatile multicontact planning and control framework (66 citations) further advances the field by enabling complex holistic movements and multiple contact interactions for loco-manipulation tasks. He has also developed methods for generating continuous motion and force plans in real-time (25 citations), addressing how manipulator contact forces affect legged systems. His work on contact-implicit trajectory optimization (20 citations) reformulates complementarity conditions for dynamic object manipulation, while his passivity-based control for haptic teleoperation (15 citations) tackles time-delay destabilization in multi-limbed mobile manipulators. With over 200 citations across his key publications, Sleiman’s contributions are shaping the next generation of agile, collision-aware robots capable of performing complex manipulation tasks in real-world environments.

Research Focus

Key Achievements

5
H-Index
7
Papers
199
Total Citations
28
Avg Citations/Paper
🏆 Most Cited Paper
A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation
69 citations · 2022
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: ETH Zurich

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago