Multi-drone cooperative transport (CT) problem has been widely studied in the literature. However, limited work exists on control of such systems in the presence of time-varying uncertainties, such as the time-varying center of gravity (CG). This paper presents a leader-follower approach for the control of a multi-drone CT system with time-varying CG. The leader uses a traditional Proportional-Integral-Derivative (PID) controller, and in contrast, the follower uses a deep reinforcement learning (RL) controller using only local information and minimal leader information. Extensive simulation results are presented, showing the effectiveness of the proposed method over a previously developed adaptive controller and for variations in the mass of the objects being transported and CG speeds. Preliminary experimental work also demonstrates ball balance (depicting moving CG) on a stick/rod lifted by two Crazyflie drones cooperatively.

翻译：多无人机协同运输（CT）问题已在文献中得到广泛研究。然而，针对此类系统在时变不确定性（如时变重心）存在情况下的控制研究尚显不足。本文提出一种面向具有时变重心的多无人机CT系统的主从控制方法。其中，主无人机采用传统比例-积分-微分（PID）控制器，而从无人机则利用仅包含局部信息及少量主无人机信息的深度强化学习控制器。大量仿真结果表明，相较于先前开发的自适应控制器，所提方法在应对运输物体质量变化及重心移动速度变化时具有显著有效性。初步实验验证了两架Crazyflie无人机协同抬升杆/棒时球体平衡（模拟移动重心）的可行性。