Dingqi Zhang — accepted AI-conference papers

2025

ProxFly: Robust Control for Close Proximity Quadcopter Flight Via Residual Reinforcement Learning

Ruiqi Zhang, Dingqi Zhang, Mark W. Mueller

ICRA 2025

This paper proposes the ProxFly, a residual deep Reinforcement Learning (RL)-based controller for close proximity quadcopter flight. Specifically, we design a residual module on top of a cascaded controller (denoted as basic controller) to generate high-level control commands, which compensate for e

Cited by 10 Source ↗code ↗Scholar ↗

2023

Learning a Single Near-hover Position Controller for Vastly Different Quadcopters

Dingqi Zhang, Antonio Loquercio, Xiangyu Wu, Ashish Kumar, Jitendra Malik, Mark W. Mueller

ICRA 2023poster

This paper proposes an adaptive near-hover position controller for quadcopters, which can be deployed to quadcopters of very different mass, size and motor constants, and also shows rapid adaptation to unknown disturbances during runtime. The core algorithmic idea is to learn a single policy that ca…

Cited by 23 Source ↗Scholar ↗