Zhiying Peng
Papers
1
Total Citations
7
H-Index
1
About
Zhiying Peng is a researcher focused on advancing autonomous robot navigation in complex, human-filled environments. Their primary research area lies at the intersection of robotics and artificial intelligence, specifically applying deep reinforcement learning to enable robots to move safely and socially through dense crowds. Peng’s most notable contribution is the development of a novel dual social attention mechanism for deep reinforcement learning, which allows a robot to simultaneously attend to the dynamic movements and social interactions of multiple pedestrians. This work, published in 2021 and garnering 7 citations, directly addresses the critical challenge of finding a collision-free path that aligns with human social norms, moving beyond simple obstacle avoidance. By modeling the complex interplay between individuals in a crowd, Peng’s research provides a more efficient and socially compliant navigation strategy, marking a significant step toward integrating robots into our daily social spaces.
Research Focus
Key Achievements
Top Papers
- 1