基于任务的多空中系统协调的信号时间逻辑方法:风力发电机检测案例研究

IF 5.2 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Robotics and Autonomous Systems Pub Date : 2025-04-01 Epub Date: 2025-01-02 DOI:10.1016/j.robot.2024.104905
Giuseppe Silano , Alvaro Caballero , Davide Liuzza , Luigi Iannelli , Stjepan Bogdan , Martin Saska
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引用次数: 0

摘要

本文研究了多旋翼机队协同巡检任务的任务分配和轨迹生成,重点研究了风力发电机巡检场景。提出的解决方案在适应不同时间约束和车辆物理限制的同时,实现了安全可行的轨迹。为了满足任务目标和时间要求,提出了一个优化问题,编码为信号时间逻辑(STL)规范。此外,还引入了事件触发的重新规划器来处理不可预见的事件并补偿损失的时间。此外,采用广义鲁棒性评分方法来反映用户偏好和缓解任务冲突。通过MATLAB和Gazebo仿真以及多机器人实地仿真验证了该方法的有效性。
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A Signal Temporal Logic approach for task-based coordination of multi-aerial systems: A wind turbine inspection case study
The paper addresses task assignment and trajectory generation for collaborative inspection missions using a fleet of multi-rotors, focusing on the wind turbine inspection scenario. The proposed solution enables safe and feasible trajectories while accommodating heterogeneous time-bound constraints and vehicle physical limits. An optimization problem is formulated to meet mission objectives and temporal requirements encoded as Signal Temporal Logic (STL) specifications. Additionally, an event-triggered replanner is introduced to address unforeseen events and compensate for lost time. Furthermore, a generalized robustness scoring method is employed to reflect user preferences and mitigate task conflicts. The effectiveness of the proposed approach is demonstrated through MATLAB and Gazebo simulations, as well as field multi-robot experiments in a mock-up scenario.
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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