Huan Ma

Huazhong University of Science and Technology

Papers

Total Citations

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About

Huan Ma is pioneering the next generation of robotic perception through advanced vision-based tactile sensing. His research centers on developing tactile sensors that give robots a sophisticated sense of touch, enabling them to perceive surface geometry, texture, and contact deformations with remarkable precision. Ma’s major contributions include the creation of GelRoller, a rolling vision-based tactile sensor that uses a self-supervised photometric stereo method to reconstruct large surface geometries—a breakthrough for robotic environmental perception. He has also advanced model-based 3D contact geometry perception for visual-tactile sensors, allowing robots to interpret complex contact shapes during manipulation. In slip detection, Ma introduced STNet, a spatio-temporal fusion-based self-attention network that significantly improves a robot’s ability to detect and prevent object slippage during dexterous tasks. His work, accumulating over 20 citations across key publications from 2022 to 2024, is shaping the future of tactile robotics by bridging high-resolution sensing with intelligent, real-time perception. Ma’s innovations are critical for applications in manufacturing, healthcare, and autonomous systems, where precise tactile feedback is essential for safe and effective robot interaction with the physical world.