Jun Peng
Papers
13
Total Citations
85
H-Index
6
About
Jun Peng is a robotics researcher whose work focuses on the critical challenge of enabling mobile robots to navigate and make decisions in complex, dynamic environments. His primary research areas include multi-robot systems, path planning, and autonomous navigation. Peng’s most significant contributions lie in developing practical, real-time solutions for trajectory generation and collision avoidance. Notably, his 2014 and 2015 papers on cooperative and suboptimal path planning for multiple mobile robot systems (MMRS), each garnering 16 citations, address the often-overlooked integration of kinematic constraints with collision-free navigation, providing a more realistic framework for robot coordination. He has also advanced state estimation techniques for robot self-localization and object tracking, introducing adaptive particle and unscented particle filters that improve performance under non-Gaussian noise. Further demonstrating his breadth, Peng has applied ant colony optimization to rescue robot path planning and developed optimal task decision methods for warehouse robots using linear temporal logic. His work consistently bridges theoretical algorithms with the practical constraints of real-world robotics, making his research highly relevant for students and engineers developing autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4A prioritized path planning algorithm for MMRS8 citations · 2014
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- 6A Rescue Robot Path Planning Based on Ant Colony Optimization Algorithm6 citations · 2009
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- 83D depth map based optimal motion control for wheeled mobile robot3 citations · 2017
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