Sen Yan
Papers
1
Total Citations
3
H-Index
1
About
Sen Yan is a rising researcher in robotics and artificial intelligence, with a primary focus on intelligent motion planning and dynamic obstacle avoidance for robotic systems. His most notable contribution is the development of a deep reinforcement learning framework with adaptive reward mechanisms, designed to enable six-degree-of-freedom robotic arms to navigate complex, changing environments while avoiding singular configurations. This work, published in 2025 and already garnering 3 citations, addresses a critical bottleneck in industrial and service robotics: the safe and flexible operation of manipulators in unpredictable settings. Yan’s approach stands out for its adaptive reward structure, which allows the robot to learn optimal paths in real time, enhancing both efficiency and safety. His research bridges the gap between theoretical reinforcement learning and practical robotic control, offering scalable solutions for automation. As an early-career scholar, Yan’s work signals a promising trajectory in embodied AI, with potential applications in manufacturing, healthcare, and autonomous systems. His innovative methodology positions him as a key contributor to the next generation of intelligent, adaptive robotics.
Research Focus
Key Achievements
Top Papers
- 1