Changhao Sun
Papers
2
Total Citations
14
H-Index
2
About
Changhao Sun is a robotics researcher whose work centers on autonomous navigation and state estimation for mobile robots operating under uncertainty. His key research areas include reinforcement learning for path planning in nondeterministic environments and robust attitude estimation under magnetic interference. Sun’s most cited paper, “Reinforcement Learning for Robot Navigation in Nondeterministic Environments” (2018, 9 citations), addresses a critical challenge in mobile robotics: enabling robots to plan paths in unknown environments where exact mathematical models are unavailable. By formulating the problem as a nondeterministic Markov decision process, he provides a framework for robots to learn adaptive behaviors for missions like target searching and security surveillance. His more recent work, “A Decoupled-DCM Orientation Estimator for Eliminating Influence of Magnetic Interference on Roll Angle and Pitch Angle” (2023, 5 citations), tackles the practical issue of real-time positioning degradation caused by motion and local magnetic field disturbances. By proposing a double-layer attitude estimator, Sun decouples roll and pitch estimation from magnetic interference, improving reliability for field robotics. Though his citation counts are modest, his contributions are foundational for robust, real-world robot autonomy.
Research Focus
Key Achievements
Top Papers
- 1
- 2