Papers
1
Total Citations
4
H-Index
1
About
Yage Shen is a robotics researcher whose work centers on legged locomotion, contact perception, and autonomous terrain adaptation for quadruped robots. His most notable contribution is the development of a probabilistic models fusion approach for contact detection, which addresses a critical challenge in legged robotics: enabling robots to perceive terrain without relying on expensive or bulky environment and foot force sensors. This work, published in 2021, has garnered 4 citations and provides a computationally efficient method for improving stability and adaptability on irregular and discontinuous ground. Shen’s research bridges the gap between sensor-limited hardware and robust real-world performance, offering practical solutions for deploying quadruped robots in unstructured environments. His contributions are particularly valuable for advancing field robotics, where cost and payload constraints often limit sensor suites. By focusing on probabilistic sensor fusion, Shen is helping to make legged robots more resilient and autonomous, paving the way for applications in search-and-rescue, exploration, and disaster response.
Research Focus
Key Achievements
Top Papers
- 1