Chengchao Bai

About

Chengchao Bai is a leading researcher in multi-robot systems, autonomous navigation, and intelligent control, with a particular focus on aerial, ground, and space robotics. His most impactful work, “Learning-Based Multi-Robot Formation Control With Obstacle Avoidance” (101 citations), introduces an adaptive framework that enables robot teams to autonomously reconfigure formations to avoid collisions—a critical capability for real-world deployment. Bai has also advanced terrain perception for planetary rovers, developing vibration-based classification and uncertainty-aware mapping methods that operate reliably under harsh conditions where vision and LiDAR fail. In the domain of defense and aerospace, his research on spatiotemporal relationship cognitive learning for multirobot air combat and deep MARL-based resilient motion planning for space manipulators addresses the complex, time-varying dynamics of autonomous confrontation and on-orbit servicing. Earlier work on human-robot cooperative assembly of large space truss structures laid groundwork for future in-space construction. With a growing portfolio spanning JetQuad aerial robots, underground localization via ground-penetrating radar, and dual-manipulator path planning for live working robots, Bai consistently pushes the boundaries of resilient, learning-driven autonomy in extreme environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Learning-Based Multi-Robot Formation Control With Obstacle Avoidance

   101 citations · 2021
2. 2
   Three-Dimensional Vibration-Based Terrain Classification for Mobile Robots

   43 citations · 2019
3. 3
   Spatiotemporal Relationship Cognitive Learning for Multirobot Air Combat

   12 citations · 2023
4. 4
   Deep MARL-Based Resilient Motion Planning for Decentralized Space Manipulator

   9 citations · 2024
5. 5
   Sequence planning for human and robot cooperative assembly of large space truss structures

   6 citations · 2017
6. 6
   Uncertainty-Based Vibration/Gyro Composite Planetary Terrain Mapping

   5 citations · 2019
7. 7
   Modeling and Control of JetQuad Aerial Robot

   4 citations · 2022
8. 8
   Research on Decoupling Motion Path Planning of Two Manipulators of Live Working Robot Based on Hybrid RRT Algorithm

   4 citations · 2021
9. 9
   Underground Robot Localization Based on Ground-Penetrating Radar

   3 citations · 2023
10. 10
    Research on Motion Path Planning Method of Live Working Robot Manipulator Based on Reverse Splitting Calculation

    3 citations · 2022

Key Collaborators

Contact & Links