In this paper, the problem of coordinated transportation of heavy payload by a team of UAVs in a cluttered environment is addressed. The payload is modeled as a rigid body and is assumed to track a pre-computed global flight trajectory from a start point to a goal point. Due to the presence of local dynamic obstacles in the environment, the UAVs must ensure that there is no collision between the payload and these obstacles while ensuring that the payload oscillations are kept minimum. An Integrated Decision Controller (IDC) is proposed, that integrates the optimal tracking control law given by a centralized Model Predictive Controller with safety-critical constraints provided by the Exponential Control Barrier Functions. The entire payload-UAV system is enclosed by a safe convex hull boundary, and the IDC ensures that no obstacle enters this boundary. To evaluate the performance of the IDC, the results for a numerical simulation as well as a high-fidelity Gazebo simulation are presented. An ablation study is conducted to analyze the robustness of the proposed IDC against practical dubieties like noisy state values, relative obstacle safety margin, and payload mass uncertainty. The results clearly show that the IDC achieves both trajectory tracking and obstacle avoidance successfully while restricting the payload oscillations within a safe limit.
翻译:本文讨论了无人驾驶航空器小组在拥挤的环境中协调运输重型有效载荷的问题。有效载荷以僵硬的机体为模范,假定从起点到目标点跟踪预先计算的全球飞行轨迹。由于环境存在当地动态障碍,无人驾驶航空器必须确保有效载荷和这些障碍之间没有碰撞,同时确保有效载荷震动保持在最低程度;提议了一个综合决定控制器(IDC),将中央集成的模拟预测控制器提供的最佳跟踪控制法与受暴露控制屏障功能提供的安全关键限制结合起来。整个有效载荷-无人驾驶航空器系统由安全的螺旋船体边界封闭起来,国际数据中心确保没有任何障碍进入这一边界。为了评价有效载荷和这些障碍的性能,提出了数字模拟的结果以及高阻燃性加泽博模拟。进行了一项综合分析,以分析拟议的国际数据中心是否稳健性,如冷却状态值、相对安全边距和有效载载载荷轨道的不稳性,同时成功地控制了轨道。