Papers
8
Total Citations
133
H-Index
5
About
M. Drouin’s research lies at the intersection of robotics, control theory, and neural network optimization, with a focus on dexterous manipulation and redundant manipulator control. His most influential work, “Real-time control of redundant robotic manipulators for mobile obstacle avoidance” (71 citations), established him as a key contributor to real-time kinematic solutions for robots operating in dynamic environments. Drouin’s major contributions include developing novel optimization frameworks for multifingered robotic hands—such as the online computation of grasping forces (22 citations) and hierarchical control structures with rolling contact compensation (6 citations)—which are fundamental to dexterous manipulation. He also pioneered penalty-based and Lyapunov-function approaches to solve inverse kinematic problems on-line, often integrating neural networks to accelerate learning and trajectory generation. His work on accelerating back-propagation and learning kinematic equations (8 citations) addressed critical bottlenecks in neural network training for robotics. Drouin’s research has provided practical, real-time solutions that bridge optimization theory and robotic control, making him a respected figure in the field of robotic manipulation and redundant systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Online computation of grasping force in multi-fingered hands22 citations · 2005
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- 7Inverse kinematic at acceleration level using neural network4 citations · 2002
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