【摘要】：針對(duì)單一傳感器在機(jī)器人避障過(guò)程中不能全面且準(zhǔn)確定位障礙物的缺點(diǎn),提出基于多傳感器信息融合的障礙物檢測(cè)方法。第一階段使用視覺(jué)傳感器檢測(cè)未知環(huán)境中的障礙物,通過(guò)Zernike矩邊緣檢測(cè)方法提取障礙物圖像邊緣,然后采用Hough變換原理提取障礙物的直線特征,獲得障礙物大概位置;第二階段使用超聲波傳感器和紅外傳感器對(duì)障礙物進(jìn)行檢測(cè),獲得障礙物準(zhǔn)確位置;最后使用聯(lián)合卡爾曼濾波對(duì)3種傳感器獲得的信息進(jìn)行融合,得出融合后的障礙物位置信息。實(shí)驗(yàn)結(jié)果表明:該方法克服視覺(jué)傳感器、超聲波傳感器和紅外傳感器的局限性,可以精確感知機(jī)器人周圍的未知環(huán)境信息,并能夠檢測(cè)和定位機(jī)器人路徑上的障礙物,定位誤差6 cm,滿足機(jī)器人避障的實(shí)時(shí)性和可靠性需求。
[Abstract]:Aiming at the shortcoming that single sensor can not locate obstacles completely and accurately in the course of robot obstacle avoidance, an obstacle detection method based on multi-sensor information fusion is proposed. In the first stage, the obstacle in unknown environment is detected by visual sensor, and the edge of obstacle image is extracted by Zernike moment edge detection method. Then the linear feature of obstacle is extracted by Hough transform principle, and the approximate position of obstacle is obtained. In the second stage, ultrasonic sensors and infrared sensors are used to detect the obstacles and obtain the exact position of the obstacles. Finally, the information obtained from the three sensors is fused by using the combined Kalman filter, and the position information of the obstacle after fusion is obtained. The experimental results show that the method overcomes the limitations of vision sensors, ultrasonic sensors and infrared sensors, and can accurately perceive the unknown environment information around the robot, and can detect and locate obstacles on the robot path. The positioning error of 6 cm, can meet the requirements of real-time and reliability of robot obstacle avoidance.
【作者單位】： 太原理工大學(xué)信息工程學(xué)院;
【分類號(hào)】：TP242;TP391.41

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本文編號(hào)：2320360