Haolin Yang
Papers
1
Total Citations
16
H-Index
1
About
Haolin Yang is a researcher at the forefront of multimodal perception for robotics, specializing in the fusion of visual and tactile sensory data to enhance robotic intelligence. His seminal work, "A framework for the fusion of visual and tactile modalities for improving robot perception" (2016), with 16 citations, introduces a pioneering framework that integrates these two critical sensory streams, enabling robots to more accurately perceive and interact with their environment. This contribution addresses a fundamental challenge in robotics: the limitations of vision alone in tasks requiring fine-grained manipulation, such as grasping delicate objects or navigating cluttered spaces. By combining visual context with tactile feedback, Yang’s framework improves object recognition and manipulation precision, laying a foundation for more adaptive and robust robotic systems. His research has implications for industrial automation, assistive robotics, and autonomous exploration. Yang’s work stands out for its practical approach to sensor fusion, bridging the gap between theoretical models and real-world robotic applications, and continues to inspire advances in embodied AI and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1