COVER: cross-vehicle transition framework for quadrotor control in air-ground cooperation
Abstract
UAV transitions across UGVs enable diverse air-ground cooperation (AGC) applications,such as cross-vehicle landing, delivery, and rescue. However, achieving precise and efficient transitions across multiple moving UGVs without prior knowledge of their trajectories remains highly challenging. This paper proposes COVER, a cross-vehicle transition frame work for quadrotor control in AGC scenarios. In COVER, the UAV is directly controlled in UGVs’ body frames as non-inertial frames, thus eliminating all dependencies in the world frame. Each transition process is divided into three stages:the initial stage, transition stage, and final stage, with pre-set stage transition points and stage-varying system states. Then,an optimal reference trajectory is generated at each stage by solving a non-linear programming (NLP) problem. The effect of the target UGV’s rotation on the initial relative velocity is eliminated to obtain a dynamically feasible and smooth transition reference trajectory. Finally, we design a stage-adaptive model predictive control (SAMPC) method, proposing a novel MPC position reference mode to avoid indirect routes at the transition stage. The SAMPC method effectively mitigates the flight instability caused by reference frame transition and eliminates the effect of reference frame rotation at the transition stage. And it can flexibly adapt to accurate requirements at the final stage by switching position reference mode and adjusting cost weights. Simulation benchmarks and extensive real-world experiments validate that our approach can achieve smooth, short-distance, and accurate cross-vehicle operations.
Qiuyu Ren 任秋予
Ph.D. student
My research interests include UAV tracking, motion planning and Model Predictive Control (MPC)
Mingwei Lai 赖明威
Master
My research interests include model predictive control and trajectory planning.
Chao Xu 许超
Full Professor
My research interests include Geometries and Control of Mechanical Systems, Kinematic Agents and Cybernetics, Multi-Physics Driven Robotics, AI-Driven Science.
Fei Gao 高飞
Associate Professor
My research interests include aerial robotics, autonomous navigation, swarm cooperation, and embodied intelligence.
Yanjun Cao 曹燕军
Research Professor
My research interests focuse on key challenges in multi-robot systems, such as collaborative localization, perception, communication, and system organization.