Peiyu Chang
Papers
1
Total Citations
2
H-Index
1
About
Peiyu Chang is a researcher specializing in robotics, with a particular focus on trajectory planning and optimization for redundant manipulators. Their key contributions lie in developing multi-objective optimization frameworks that enhance the efficiency and safety of robotic systems. In their most-cited work, "Trajectory planning based on multi-objective optimization for redundant robots" (2016), Chang introduced a novel method that integrates obstacle avoidance potential functions as inequality constraints, enabling robots to navigate complex environments while optimizing performance metrics. This work, cited 2 times, addresses critical challenges in industrial and service robotics, such as collision avoidance and energy efficiency. Chang’s research is notable for bridging theoretical optimization with practical robotic applications, offering solutions that improve both autonomy and reliability. Their contributions are particularly valuable for students and researchers exploring advanced control strategies in robotics, as they provide a foundation for further innovation in autonomous systems and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1