论文标题
在混乱的环境中合作安全至关重要有效载荷运输的综合决策控制方法
Integrated Decision Control Approach for Cooperative Safety-Critical Payload Transport in a Cluttered Environment
论文作者
论文摘要
在本文中，解决了无人机团队在混乱环境中协调运输重大有效载荷的问题。有效载荷被建模为刚体的身体，并被认为可以跟踪从起点到目标点的预计全球飞行轨迹。由于环境中存在局部动态障碍，无人机必须确保有效载荷与这些障碍之间没有碰撞，同时确保有效载荷振荡保持最小。提出了一个集成的决策控制器（IDC），该决策控制器（IDC）集成了集中式模型预测控制器给出的最佳跟踪控制法，并与指数控制屏障功能提供的安全至关重要约束。整个有效载荷-UAV系统被安全的凸面边界所包围，IDC确保没有障碍进入此边界。为了评估IDC的性能，提供了数值模拟以及高保真凉亭模拟的结果。进行了一项消融研究，以分析拟议的IDC对诸如嘈杂状态值，相对障碍安全余量和有效载荷质量不确定性等实用性的稳健性。结果清楚地表明，IDC在安全限制内限制有效载荷振荡时成功地实现了轨迹跟踪和障碍避免。
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.
