Yiqian Teng
Papers
1
Total Citations
10
H-Index
1
About
Yiqian Teng is a researcher focused on advancing assistive robotics through learning from demonstration, with a particular emphasis on improving quality of life for elderly and disabled individuals. Their most-cited work, "Learning motion primitives from demonstration" (2017), introduces a method that enables robotic systems—such as intelligent wheelchairs—to acquire and generalize complex movement skills by observing human demonstrations. This approach enhances the adaptability and intelligence of assistive devices, allowing them to better support users in activities of daily living. By bridging robot learning and practical caregiving, Teng's contributions address critical challenges in human-robot interaction and autonomous assistance. With 10 citations, this foundational paper has informed subsequent research in motion planning and imitation learning for healthcare robotics. Teng's work stands out for its direct application to real-world needs, offering a pathway toward more intuitive and responsive assistive technologies that empower individuals with limited mobility.
Research Focus
Key Achievements
Top Papers
- 1Learning motion primitives from demonstration10 citations · 2017