联网空中智能体团队协同滚动时域三维覆盖控制
Cooperative Receding Horizon 3D Coverage Control with a Team of Networked Aerial Agents
AI总结：
本研究针对多空中智能体三维物体协同覆盖问题，提出滚动时域控制方法，通过将可见性约束转化为逻辑约束嵌入混合整数优化，联合优化运动与相机输入并减少重复作业。
摘要：
本研究提出一种滚动时域覆盖控制方法，可使多个自主空中智能体协同作业，以覆盖目标三维物体的全部表面积。本文将协同覆盖问题构建为最优控制问题，在考虑智能体团队间旨在最小化重复作业的耦合约束的同时，联合优化智能体的运动学与相机控制输入。为在有限规划时域内生成前瞻覆盖轨迹，所提方法将可见性约束整合至所提出的覆盖控制器中，以确定物体相对于智能体未来状态的可见部分。具体而言，我们展示了如何将非线性、非凸的可见性判定约束转化为可轻松嵌入混合整数优化程序的逻辑约束。
英文摘要：
This work proposes a receding horizon coverage control approach which allows multiple autonomous aerial agents to work cooperatively in order cover the total surface area of a 3D object of interest. The cooperative coverage problem which is posed in this work as an optimal control problem, jointly optimizes the agents' kinematic and camera control inputs, while considering coupling constraints amongst the team of agents which aim at minimizing the duplication of work. To generate look-ahead coverage trajectories over a finite planning horizon, the proposed approach integrates visibility constraints into the proposed coverage controller in order to determine the visible part of the object with respect to the agents' future states. In particular, we show how non-linear and non-convex visibility determination constraints can be transformed into logical constraints which can easily be embedded into a mixed integer optimization program.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
