Jorge de Heuvel
Papers
10
Total Citations
87
H-Index
5
About
Jorge de Heuvel is a robotics researcher whose work sits at the intersection of robot navigation, reinforcement learning, and human-robot interaction. His research focuses on developing intelligent, adaptive navigation systems that can operate safely and comfortably alongside humans in dynamic environments — a challenge that demands both technical sophistication and sensitivity to human preferences. De Heuvel's most impactful contribution, "Spatiotemporal Attention Enhances Lidar-Based Robot Navigation in Dynamic Environments" (2024, 26 citations), demonstrates his ability to design lightweight yet powerful controllers that infer scene dynamics without costly explicit object tracking. A recurring theme across his work is personalization: his virtual reality-based demonstration frameworks allow robots to learn individual user preferences, bridging the gap between generic navigation policies and truly human-aware systems, earning significant community recognition with 16 and 14 citations respectively. His research also extends into sparse reward reinforcement learning, explainable AI for robot decision-making, and precision robotic manipulation. Notably, his RHINO-VR museum exhibit project reflects a commitment to public robotics education. With over 85 total citations across recent publications, de Heuvel has established himself as a promising and prolific voice in the field of socially intelligent autonomous robotics.
Research Focus
Key Achievements
Top Papers
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