Papers
7
Total Citations
181
H-Index
6
About
Guillaume Morel is a prominent robotics researcher whose work spans human-robot interaction, vision-based control, and medical robotics. His research has made significant contributions to how robots perceive, predict, and respond to human movement, with lasting implications for both assistive technologies and surgical robotics. Morel's most influential work, "How can human motion prediction increase transparency?" (2008, 74 citations), addressed a fundamental challenge in assistive robotics: enabling robots to follow human movements without generating resistive forces, a property known as transparency. This contribution helped shape modern thinking in collaborative human-robot manipulation. His earlier work on vision-based control, particularly his 2000 paper on incorporating 2D constraints into robot manipulator control (57 citations), established robust frameworks for guiding robotic arms using visual feedback — a cornerstone capability in modern robotics. His research extended powerfully into surgical applications, including visual servoing for minimally invasive surgery, ultrasound-guided instrument tracking, and automated laparoscopic positioning. More recently, he explored exoskeleton trajectory computation for upper limb rehabilitation, bridging biomechanics and assistive robotics. Through projects like PROSBOT, Morel also demonstrated a commitment to translating research into clinical contexts. Collectively, his body of work reflects a career dedicated to making robots safer, smarter, and more intuitive partners for human users.
Research Focus
Key Achievements
Top Papers
- 1How can human motion prediction increase transparency?74 citations · 2008
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- 3Robust vision based 3D trajectory tracking using sliding mode control18 citations · 2002
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- 7PROSBOT – Model and image controlled prostatic robot3 citations · 2015