Chensheng Cheng

Papers

Total Citations

H-Index

About

Chensheng Cheng is a researcher specializing in autonomous robotics, with a focus on path planning, multi-robot coordination, and control systems in GPS-denied environments. His most notable contribution is a reinforcement learning-based path planning method that integrates error estimation, addressing the critical challenge of accumulated odometry sensor drift in environments without satellite navigation. This work, published in 2021 and cited 13 times, enhances the reliability of autonomous driving and robotic navigation by combining learning-based decision-making with real-time uncertainty quantification. Cheng also advanced multi-robot systems through his 2019 study on wall-following control, which employs moving target tracking and obstacle avoidance strategies to enable coordinated behavior among multiple agents. His research bridges theoretical reinforcement learning with practical robotic applications, offering robust solutions for real-world deployment. With a growing citation record, Cheng’s work is increasingly recognized for its impact on autonomous navigation in challenging settings, making him a promising contributor to the field of intelligent robotics.