Papers
14
Total Citations
384
H-Index
9
About
Olivier Kermorgant is a robotics researcher whose work spans sensor-based control, multi-robot systems, and autonomous manipulation, with contributions that have shaped modern approaches to robot perception and cooperative task execution. His foundational work on multi-sensor fusion for robot control, notably his 2013 framework for managing constrained multisensor systems (61 citations) and earlier investigations into multi-camera visual servoing (33 citations), established robust theoretical tools for handling complex, real-world sensor environments. Kermorgant has demonstrated a strong talent for bridging theory and application: his 2018 study on a magnetic climbing robot for autonomous shipbuilding welding (106 citations) stands as his most impactful contribution, illustrating how advanced robotics can transform industrial practice. His research into cooperative multi-robot logistics, particularly optimization-based formation control (75 citations) and consensus-driven obstacle avoidance, addresses the growing demand for scalable autonomous systems in warehouse and transportation settings. Additional contributions to underwater vehicle-manipulator simulation, cable-driven parallel robots, and predictive control for autonomous parking reflect the impressive breadth of his expertise. Across more than a decade of research, Kermorgant has built a body of work that meaningfully advances both the theoretical foundations and practical deployment of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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- 3Dealing With Constraints in Sensor-Based Robot Control61 citations · 2013
- 4A Dynamic Simulator for Underwater Vehicle-Manipulators34 citations · 2014
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- 8Cable-Driven Parallel Robot Simulation Using Gazebo and ROS14 citations · 2018
- 9Multisensor-Based Predictive Control for Autonomous Parking11 citations · 2021
- 10Avoiding joint limits with a low-level fusion scheme4 citations · 2011