Peiyan Yang
Papers
1
Total Citations
6
H-Index
1
About
Peiyan Yang is a rising researcher in robotics and autonomous navigation, with a primary focus on developing efficient, collision-free path planning algorithms for dynamic and constrained environments. Their most cited work, "APF-IBRRT*: A Global Path Planning Algorithm for Obstacle Avoidance Robots With Improved Iterative Search Efficiency" (2024, 6 citations), addresses a critical limitation of the widely-used Rapidly-exploring Random Tree (RRT) algorithm. While RRT and its variants are valued for their asymptotically optimal solutions, they struggle in narrow, cluttered indoor spaces where iterative search efficiency degrades. Yang’s contribution integrates Artificial Potential Fields (APF) with an improved bidirectional RRT* framework, significantly enhancing convergence speed and path smoothness without sacrificing collision avoidance. This hybrid approach offers a practical, real-time solution for service and industrial robots operating in tight quarters. Though early in their career, Yang’s work has already garnered attention for its direct applicability to real-world obstacle avoidance challenges. Their research sits at the intersection of sampling-based planning, heuristic optimization, and reactive control, promising further advances in autonomous navigation for complex indoor environments.
Research Focus
Key Achievements
Top Papers
- 1