有效载荷(计算)
敏捷软件开发
计算机科学
弹道
运动规划
机器人
非线性系统
控制工程
工程类
人工智能
计算机网络
天文
量子力学
软件工程
物理
网络数据包
作者
Haokun Wang,Haojia Li,Boyu Zhou,Fei Gao,Shaojie Shen
标识
DOI:10.1109/tro.2024.3381555
摘要
A quadrotor with a cable-suspended payload imposes great challenges in impact-aware planning and control. This joint system has dual motion modes, depending on whether the cable is slack or not, and presents complicated dynamics. Therefore, generating feasible agile flight while preserving the retractable nature of the cable is still a challenging task. In this paper, we propose a novel impact-aware planning and control framework that resolves potential impacts caused by motion mode switching. Our method leverages the augmented Lagrangian method (ALM) to solve an optimization problem with nonlinear complementarity constraints (ONCC), which ensures trajectory feasibility with high accuracy while maintaining efficiency. We further propose a hybrid nonlinear model predictive control method to address the model mismatch issue in agile flight. Our methods have been comprehensively validated in both simulation and experiments, demonstrating superior performance compared to existing approaches. To the best of our knowledge, we are the first to successfully perform automatic multiple motion mode switching for aerial payload systems in real-world experiments. The video supplement is available at https://sites.google.com/view/suspended-payload/ .
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