Chao-Chung Peng

About

Chao-Chung Peng is a leading researcher in intelligent robotics and autonomous navigation, with a focus on enabling robots to operate reliably in complex, real-world environments. His primary research areas include path smoothing, simultaneous localization and mapping (SLAM), multi-robot coordination, and robust control systems. Peng’s most impactful contribution is his comprehensive survey on path smoothing techniques for robot navigation, which has garnered 299 citations and serves as a foundational reference for the field. He has also pioneered a single LiDAR-based feature fusion algorithm for indoor localization (83 citations), significantly reducing system cost and computational load. His work on a robust 2D-SLAM system (33 citations) addresses the challenge of environmental variation, enhancing robot adaptability. Peng’s innovative approaches extend to nonlinear observer design for state estimation and unknown input reconstruction, as well as symbiotic multi-robot navigation schemes. His recent exploration of deep reinforcement learning for collision avoidance in unmanned aerial vehicles demonstrates his forward-looking vision. With a consistent record of high-impact publications, Peng’s research continues to shape the future of autonomous mobile robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges

   299 citations · 2018
2. 2
   A Single LiDAR-Based Feature Fusion Indoor Localization Algorithm

   83 citations · 2018
3. 3
   A Robust 2D-SLAM Technology With Environmental Variation Adaptability

   33 citations · 2019
4. 4
   Robust trajectories following control of a 2-link robot manipulator via coordinate transformation for manufacturing applications

   14 citations · 2010
5. 5
   Nonlinear Integral Type Observer Design for State Estimation and Unknown Input Reconstruction

   12 citations · 2017
6. 6
   Hitchhiking Based Symbiotic Multi-Robot Navigation in Sensor Networks

   12 citations · 2018
7. 7
   LIDAR based scan matching for indoor localization

   11 citations · 2017
8. 8
   An integral method for parameter identification of a nonlinear robot subject to quantization error

   9 citations · 2023
9. 9
   Task coordination for multiple mobile robots considering semantic and topological information

   6 citations · 2018
10. 10
    Deep reinforcement learning–based collision avoidance strategy for multiple unmanned aerial vehicles

    5 citations · 2025

Key Collaborators

Contact & Links