IARC第7代任務(wù)中定位與目標(biāo)跟蹤方法研究
發(fā)布時(shí)間：2018-10-09 21:26
【摘要】：空中機(jī)器人在航拍、運(yùn)輸、巡檢、搜救等領(lǐng)域有廣泛應(yīng)用,其定位、導(dǎo)航和目標(biāo)跟蹤技術(shù)也成為研究熱點(diǎn)。國(guó)際空中機(jī)器人大賽是最具挑戰(zhàn)性的無人機(jī)賽事之一,大賽目的是推動(dòng)空中機(jī)器人技術(shù)發(fā)展,其任務(wù)都是當(dāng)前無人機(jī)技術(shù)所不能達(dá)到的,參與和研究比賽任務(wù)有重要意義,本文在大賽第7代任務(wù)背景下展開,主要工作和創(chuàng)新如下所述。1.根據(jù)比賽任務(wù),搭建了智能四旋翼平臺(tái)。平臺(tái)利用機(jī)載電腦實(shí)現(xiàn)視覺定位、目標(biāo)跟蹤、避障等上層功能,針對(duì)遙控和程序控制的切換問題,設(shè)計(jì)了手自動(dòng)切換系統(tǒng),系統(tǒng)由STM32單片機(jī)接收遙控器和機(jī)載電腦指令,根據(jù)遙控器手自動(dòng)切換檔位,將相應(yīng)遙控或程序控制指令傳給下層飛控。該四旋翼平臺(tái)既能應(yīng)用于比賽場(chǎng)景,也可用于巡檢、救援等其他場(chǎng)合。2.基于單目視覺和IMU開發(fā)了定位與懸停系統(tǒng)。該系統(tǒng)利用光流法對(duì)飛行器運(yùn)動(dòng)速度進(jìn)行估計(jì),并結(jié)合卡爾曼濾波算法實(shí)現(xiàn)了光流速度與IMU信息的數(shù)據(jù)融合,提高了飛行器速度估計(jì)的精度和平滑性,同時(shí)基于速度信息設(shè)計(jì)了位置速度串級(jí)控制器,實(shí)現(xiàn)了飛行器的視覺懸停。此外,針對(duì)光流法積分存在累計(jì)誤差的問題,提出了一種基于比賽場(chǎng)地方格和張正友相機(jī)標(biāo)定法的視覺定位方案,詳細(xì)闡述了方案原理,并進(jìn)行了可行性分析。3.針對(duì)單目標(biāo)識(shí)別、跟蹤與觸碰問題,提出了一種綜合解決方案。該方案利用CamShift算法進(jìn)行單目標(biāo)識(shí)別,利用PID控制器進(jìn)行目標(biāo)跟蹤,并采用基于開關(guān)控制的高度控制器實(shí)現(xiàn)觸碰。在AR.Drone四旋翼上進(jìn)行了實(shí)驗(yàn),驗(yàn)證了算法的有效性,實(shí)現(xiàn)了比賽內(nèi)容中的單目標(biāo)驅(qū)趕目標(biāo)。4.針對(duì)比賽場(chǎng)地存在多個(gè)運(yùn)動(dòng)目標(biāo)的情況,設(shè)計(jì)了基于移動(dòng)目標(biāo)顏色特征及最近鄰算法的多目標(biāo)檢測(cè)器與跟蹤器,提出了基于移動(dòng)目標(biāo)顏色區(qū)域形狀特征的目標(biāo)朝向檢測(cè)算法。實(shí)驗(yàn)表明了算法的有效性。相關(guān)實(shí)驗(yàn)視頻在優(yōu)酷頻道(http://i.youku.com/u/UMzMwMDg3NTAlMg==/videos)中,可下載瀏覽。
[Abstract]:Aerial robots are widely used in aerial photography, transportation, inspection, search and rescue, and so on. The international aerial robot competition is one of the most challenging UAV competitions. The purpose of the competition is to promote the development of aerial robot technology, and its tasks are beyond the reach of the current UAV technology. It is of great significance to participate in and study the competition tasks. This paper is carried out in the context of the 7th generation task, the main work and innovation described below. 1. According to the task of the competition, the intelligent four-rotor platform is built. The platform uses the airborne computer to realize the upper functions such as visual positioning, target tracking, obstacle avoidance and so on. Aiming at the switching problem of remote control and program control, a hand-automatic switching system is designed. The system receives remote control and airborne computer instructions by STM32 microcontroller. According to the remote control hand automatically switch gear, the corresponding remote control or program control instructions to the lower flight control. The four-rotor platform can be used not only in competition scenes, but also in inspection, rescue and other occasions. 2. A positioning and hovering system is developed based on monocular vision and IMU. The system uses the optical flow method to estimate the velocity of the vehicle, and combines the Kalman filter algorithm to realize the data fusion of the optical flow velocity and the IMU information, which improves the accuracy and smoothness of the vehicle velocity estimation. At the same time, the position speed cascade controller is designed based on the velocity information, which realizes the visual hovering of the aircraft. In addition, aiming at the problem of accumulative error in the integration of optical flow method, this paper presents a visual positioning scheme based on the grid of competition site and the calibration method of Zhang Zhengyou camera. The principle of the scheme is described in detail, and the feasibility analysis is made. Aiming at the problem of single target recognition, tracking and touching, a comprehensive solution is proposed. In this scheme, CamShift algorithm is used for single target recognition, PID controller is used for target tracking, and height controller based on switch control is used to realize contact. Experiments are carried out on the AR.Drone four-rotor, the validity of the algorithm is verified, and the single-target drive target .4in the content of the competition is realized. In view of the situation that there are many moving targets in the competition field, a multi-target detector and tracker based on moving object color feature and nearest neighbor algorithm is designed, and a target orientation detection algorithm based on the shape feature of moving target color region is proposed. Experiments show the effectiveness of the algorithm. The video about the experiment is available for download on Youku Channel (http://i.youku.com/u/UMzMwMDg3NTAlMg==/videos).
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41
[Abstract]:Aerial robots are widely used in aerial photography, transportation, inspection, search and rescue, and so on. The international aerial robot competition is one of the most challenging UAV competitions. The purpose of the competition is to promote the development of aerial robot technology, and its tasks are beyond the reach of the current UAV technology. It is of great significance to participate in and study the competition tasks. This paper is carried out in the context of the 7th generation task, the main work and innovation described below. 1. According to the task of the competition, the intelligent four-rotor platform is built. The platform uses the airborne computer to realize the upper functions such as visual positioning, target tracking, obstacle avoidance and so on. Aiming at the switching problem of remote control and program control, a hand-automatic switching system is designed. The system receives remote control and airborne computer instructions by STM32 microcontroller. According to the remote control hand automatically switch gear, the corresponding remote control or program control instructions to the lower flight control. The four-rotor platform can be used not only in competition scenes, but also in inspection, rescue and other occasions. 2. A positioning and hovering system is developed based on monocular vision and IMU. The system uses the optical flow method to estimate the velocity of the vehicle, and combines the Kalman filter algorithm to realize the data fusion of the optical flow velocity and the IMU information, which improves the accuracy and smoothness of the vehicle velocity estimation. At the same time, the position speed cascade controller is designed based on the velocity information, which realizes the visual hovering of the aircraft. In addition, aiming at the problem of accumulative error in the integration of optical flow method, this paper presents a visual positioning scheme based on the grid of competition site and the calibration method of Zhang Zhengyou camera. The principle of the scheme is described in detail, and the feasibility analysis is made. Aiming at the problem of single target recognition, tracking and touching, a comprehensive solution is proposed. In this scheme, CamShift algorithm is used for single target recognition, PID controller is used for target tracking, and height controller based on switch control is used to realize contact. Experiments are carried out on the AR.Drone four-rotor, the validity of the algorithm is verified, and the single-target drive target .4in the content of the competition is realized. In view of the situation that there are many moving targets in the competition field, a multi-target detector and tracker based on moving object color feature and nearest neighbor algorithm is designed, and a target orientation detection algorithm based on the shape feature of moving target color region is proposed. Experiments show the effectiveness of the algorithm. The video about the experiment is available for download on Youku Channel (http://i.youku.com/u/UMzMwMDg3NTAlMg==/videos).
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41
【參考文獻(xiàn)】
相關(guān)期刊論文 前3條
1 曹美會(huì);鮮斌;張旭;文曦;;基于視覺的四旋翼無人機(jī)自主定位與控制系統(tǒng)[J];信息與控制;2015年02期
2 張梁;徐錦法;;基于雙目視覺的無人飛行器目標(biāo)跟蹤與定位[J];計(jì)算機(jī)工程與應(yīng)用;2014年24期
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