Cao Muqing

Cao Muqing

Postdoc, Carnegie Mellon University Ph.D, Nanyang Technological University

Muqing Cao’s Home Page

Hi, I am a postdoctoral fellow at Robotics Institute, Carnegie Mellon University. I obtained my PhD and bachelor degree from Nanyang Technology University, Singapore. My research interests are aerial robots, multi-robot planning, robot dynamics, and control. If you are interested in my research, please contact me via email: caom0006 AT e.ntu.edu.sg.

I am very interested in collaborating with/mentoring students in research. Please feel free to drop me an email and set up a call if you would like to discuss research problems or seek research guidance.

News

  • 2024/10
    I have started a position as a postdoctor at CMU AirLab!
  • 2024/10
    We successfully organized IROS 2024 Workshop and Competition on Multi-Robot Perception and Navigation Challenges in Logistics and Inspection Tasks (website). Thanks to all speakers and participants!
  • 2024/06
    We are organizing the Cooperative Aerial Robots Inspection Challenge (CARIC) (website) in conjunction with IROS 2024 Workshop!
  • 2024/06
    Our paper on a novel hybrid aerial-ground manipulator has been accepted by IROS 2024!
  • 2023/10
    Our paper on a novel hybrid aerial-ground robot has been awarded the IROS 2023 Best Entertainment Paper!
  • 2023/03
    Our paper on trajectory planning multi-tethered robots has been accepted by T-RO!

Highlights

Trajectory Planning for Multiple Tethered Unmanned Vehicles (IEEE T-RO)

We introduced a trajectory planning framework for multiple tethered unmanned vehicles. The framework lewverages a proposed representation of homotopy that efficiently captures the interactions among the robots, and generates trajectories in an online and decentralized manner.

[Paper][Video][Code]

Learning Weighted Trajectory Planning in Crowd (Submitted to ICRA 2025)

we propose a dynamic weight adjustment scheme using a neural network to predict the optimal weights of objectives in an optimization-based motion planner.


[Paper][Video]

AirCrab: A Hybrid Aerial-Ground Manipulator (IROS 2024)

AirCrab is a hybrid aerial ground manipulator (HAGM) with an active wheel and a 3-DoF manipulator. AirCrab leverages a single point of contact with the ground to reduce position drift and improve manipulation accuracy.

[Paper][Video]

Cooperative Aerial Robots Inspection Challenge (CARIC) @ CDC 2023

We have organized a simulation-based challenge to design efficient solutions for multi-UAV collaborative inspection of large structures. The winners will be announced at IEEE Conference on Decision and Control (CDC), Singapore, December 2023.

[Challenge Rules]

A New Hybrid Aerial-Ground Robot (IROS 2023 Best Entertainment Paper)

We introduced a novel hybrid aerial-ground robot capable of climbing slope, flying over obstacles and crawling under barriers. IROS Best Entertainment and Amusement Paper Award sponsored by JTCF.

[Paper][Video]

Planning for Multiple Tethered Robots Using Topological Braids (RSS 2023)

We proposed a path planning algorithm for multiple tethered robot with guaranteed non-entanglement, leveraging the theory of topological braids.


[Paper][Video][Presentation][Code]

Distributed Multi-Robot Sweep Coverage Control (T-SMC)

We introduced a coverage control algorithm for multi-robot sweep coverage in a region with unknown and uneven workload distribution. The paper is accepted by IEEE T-SMC. [Paper][Video]

Differential Dynamic Programming-Based Polynomial Trajectory Generation (RA-L)

We introduced a novel polynomial trajectory optimization algorithm leveraging differential dynamic programming. We have also released a solver-free implementation of the algorithm in the package. The algorithm is verified using an UAV in indoor flight experiments. The paper is accepted by IEEE RA-L. [Paper][Video][Code]