Brian Delhaisse
Italian Institute of Technology, Université Libre de Bruxelles
Papers
5
Total Citations
111
H-Index
5
About
Brian Delhaisse is a leading researcher in robot learning and human-robot interaction, with a focus on making robotic systems more accessible and adaptable. His work spans teleoperation, transfer learning, and control software design. Delhaisse’s most notable contribution is the development of a bi-manual teleoperation system using a low-cost RGB-D sensor, enabling intuitive control of articulated robots through 3D skeleton extraction—a breakthrough that has garnered 42 citations. He also pioneered transfer learning methods that allow robots with similar kinematic structures to share latent spaces, reducing the need for extensive retraining and earning 33 citations. His work on overdesign in swarm robotics (16 citations) and neural-network-controlled templates for humanoid running (8 citations) further demonstrates his versatility. Delhaisse is also the creator of PyRoboLearn, a Python framework designed to streamline robot learning for practitioners, which has already attracted 12 citations. His contributions are shaping more efficient, cost-effective, and collaborative robotic systems, making him a key figure in advancing practical robot learning and teleoperation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4PyRoboLearn: A Python Framework for Robot Learning Practitioners.12 citations · 2019
- 5Neural-Network-Controlled Spring Mass Template for Humanoid Running8 citations · 2018