Intelligent Robot Obstacle Avoidance Perception Method Using a High-Precision Laser Distance Measuring System

避障 计算机科学 激光器 信号(编程语言) 控制器(灌溉) 光学 计算机视觉 声学 人工智能
作者
Yuzhou Liu
出处
期刊:Journal of Nanoelectronics and Optoelectronics [American Scientific Publishers]
卷期号:16 (3): 471-478
标识
DOI:10.1166/jno.2021.2968
摘要

Laser distance measuring is increasingly used in large-scale and real-time scanning measurement, including three-dimensional map construction, size measurement of large-scale buildings, and real-time surface information acquisition. Therefore, there are high-precision and high-efficiency requirements for the laser distance measuring system. Based on the phase laser distance measuring, a laser parallel distance measuring system is proposed as per the frequency division multiplexer principle. The system uses multi-channel modulation signals with different frequencies to drive multiple lasers to emit light intensity in parallel, and then the light wave is measured according to the change of the modulation signal. The single-channel modulation signal adopts the multi-scale composite wave to eliminate the uncertainty of the whole wavelength by using the combination of two scales and distance measurement. The multiple echo signals after diffuse reflection of the measured target are mixed and received by the same photodetector and go through signal amplification, clutter filtering, etc., and then are sent to the mixing unit together with the reference signal, followed by down-frequency processing, with the effective signal obtained through the low-frequency filter. In the experiment, the laser distance measuring system is used for obstacle avoidance control of mobile robots, and fuzzy control is used to design the corresponding obstacle avoidance controller. The robot lateral deviation and heading angle are used as the input of the fuzzy controller, and the track variation is the output. The test verifies that the obstacle avoidance control is effective, that is, the laser distance measuring system designed in this research can be used for the obstacle avoidance control of mobile robots.

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