Pengda Mao

According to our database, Pengda Mao authored at least 11 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Virtual-Tube-Based Cooperative Transport Control for Multi-UAV Systems in Constrained Environments.

Runxiao Liu, Pengda Mao, Xiangli Le, Shuang Gu, Yapeng Chen, Quan Quan

CoRR, February, 2026

Distributed Network Control of Multi-UAV Systems for Cooperative Heavy-Load Transport Using a Virtual-Passivity Framework.

Runxiao Liu, Xiangli Le, Shuang Gu, Shuli Lv, Pengda Mao, Quan Quan

IEEE Trans. Netw. Sci. Eng., 2026

Time-Optimal Iterative Learning Planning for Lagrangian Systems and Its Application to Quadcopters.

Shuli Lv, Pengda Mao, Chen Min, Li Hong, Yan-Jun Liu, Quan Quan

IEEE Trans Autom. Sci. Eng., 2026

2025

Practical Distributed Control for Cooperative VTOL UAVs Within a 3-D Roundabout.

Rao Fu, Pengda Mao, Yangqi Lei, Kai-Yuan Cai, Quan Quan

IEEE Trans. Intell. Transp. Syst., July, 2025

An Efficient Real-Time Planning Method for Swarm Robotics Based on an Optimal Virtual Tube.

Pengda Mao, Shuli Lv, Chen Min, Zhaolong Shen, Quan Quan

CoRR, May, 2025

Tube RRT*: Efficient Homotopic Path Planning for Swarm Robotics Passing-Through Large-Scale Obstacle Environments.

Pengda Mao, Shuli Lv, Quan Quan

IEEE Robotics Autom. Lett., March, 2025

2024

Optimal virtual tube planning and control for swarm robotics.

Pengda Mao, Rao Fu, Quan Quan

Int. J. Robotics Res., 2024

Mean-Field Based Time-Optimal Spatial Iterative Learning Within a Virtual Tube.

Shuli Lv, Pengda Mao, Quan Quan

IEEE Control. Syst. Lett., 2024

Tube-RRT*: Efficient Homotopic Path Planning for Swarm Robotics Passing-Through Large-Scale Obstacle Environments.

Pengda Mao, Quan Quan

CoRR, 2024

2022

Making Robotics Swarm Flow More Smoothly: A Regular Virtual Tube Model.

Pengda Mao, Quan Quan

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

Fast Light Show Design Platform for K-12 Children.

Pengda Mao, Yan Gao, Bo Wang, An Yan, Xiaoyu Chi, Quan Quan

Proceedings of the IEEE International Conference on Robotics and Automation, 2021