基于机器视觉和多传感器融合的无人机巡逻路径规划

IF 1.1 Q3 COMPUTER SCIENCE, THEORY & METHODS Open Computer Science Pub Date : 2023-01-01 DOI:10.1515/comp-2022-0276
Xu Chen
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引用次数: 0

摘要

摘要随着无人机技术的飞速发展,无人机的应用领域越来越多。本文主要研究了基于机器视觉和多传感器融合的无人机巡逻路径规划。本文研究了如何将超声波这一经典测距传感器应用于无人机避障。所设计的超声波避障系统是一套完整的硬件和软件系统。硬件部分由正向超声模块和中央信号处理模块组成。其中,前向超声模块设计了单轴稳定框架,实现了无人机姿态角与超声传感器俯仰探测角的解耦。在中央信号处理模块中,对前、后、左、右、左四个方向的超声波数据进行卡尔曼滤波,并根据滤波后的传感器数据向飞行控制器发送避障控制信号。同时,设计了人机交互界面,对避障系统的各项参数进行设置。铁塔线路规划方法采用常规步骤,采用单线检查铁塔,具体检查对象为绝缘子串、地线和导体。在本研究中,无人机巡航100 m直线距离的平均统计结果为99.80 m,误差仅为0.2%。基于机器视觉的融合避障控制方法适合于无人机感知避障的工程应用。本文采用的避障方法可以推广到大多数飞控平台,是一种具有广阔应用前景的控制方法。
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UAV patrol path planning based on machine vision and multi-sensor fusion
Abstract With the rapid development of unmanned aerial vehicle (UAV) technology, there are more and more fields of UAV application. This research mainly discusses the UAV patrol path planning based on machine vision and multi-sensor fusion. This article studies how to apply ultrasonic, a classic ranging sensor, to obstacle avoidance of UAVs. The designed ultrasonic obstacle avoidance system is a complete set of hardware and software systems. The hardware part consists of a forward ultrasonic module and a central signal processing module. Among them, a single-axis stabilization gimbal is designed for the forward ultrasonic module, which decouples the attitude angle of the UAV and the pitch detection angle of the ultrasonic sensor. In the central signal processing module, Kalman filtering is performed on the ultrasonic data in the four directions of front, rear, left, right, and left, and the obstacle avoidance control signal is sent to the flight controller according to the filtered sensor data. At the same time, a human–computer interaction interface is also designed to set various parameters of the obstacle avoidance system. For the route planning method of the tower, the routine steps are used to inspect the tower with a single-circuit line, and the specific targets are the insulator string, the ground wire, and the conductor. In this study, the average statistical result of the straight-line distance of the UAV patrolling 100 m is 99.80 m, and the error is only 0.2%. The fusion obstacle avoidance control method based on machine vision is suitable for the engineering application of UAV perception obstacle avoidance. The obstacle avoidance method adopted in this article can be extended to most flight control platforms, and it is a control method with broad application prospects.
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来源期刊
Open Computer Science
Open Computer Science COMPUTER SCIENCE, THEORY & METHODS-
CiteScore
4.00
自引率
0.00%
发文量
24
审稿时长
25 weeks
期刊最新文献
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