發(fā)布時(shí)間：2018-05-29 02:49

  本文選題：六足機(jī)器人 + 雙目視覺(jué)��； 參考：《哈爾濱工業(yè)大學(xué)》2016年博士論文

【摘要】：六足機(jī)器人與其他輪式移動(dòng)機(jī)器人相比,具有較強(qiáng)的地形適應(yīng)能力和良好的運(yùn)動(dòng)穩(wěn)定性,在軍事偵察、搶險(xiǎn)救災(zāi)、星際探索、反恐爆破、考古探測(cè)等多個(gè)領(lǐng)域都開(kāi)始展現(xiàn)其作用。六足機(jī)器人在適應(yīng)復(fù)雜環(huán)境、獨(dú)立完成作業(yè)方面的能力是亟待解決的關(guān)鍵問(wèn)題。課題研究將以解決六足機(jī)器人復(fù)雜環(huán)境自主運(yùn)動(dòng)問(wèn)題為出發(fā)點(diǎn),重點(diǎn)攻克實(shí)時(shí)性環(huán)境建模、自主定位及運(yùn)動(dòng)規(guī)劃三個(gè)基礎(chǔ)理論難題,最終以典型復(fù)雜作業(yè)環(huán)境應(yīng)用為示范,驗(yàn)證所取得的提高機(jī)器人復(fù)雜環(huán)境下自主運(yùn)動(dòng)能力的理論與技術(shù)創(chuàng)新成果。為解決立體匹配中匹配速度與匹配精度相互制約的問(wèn)題,提出一種基于支撐點(diǎn)的立體匹配算法。首先,對(duì)攝像機(jī)采集到的原始圖像進(jìn)行極線校正,確保待匹配圖像對(duì)的對(duì)應(yīng)特征點(diǎn)在同一極線上。其次使用Canny邊緣檢測(cè)算子求取攝像機(jī)左圖像的邊緣點(diǎn)作為穩(wěn)定支撐點(diǎn),應(yīng)用分治法對(duì)支撐點(diǎn)集進(jìn)行2D Delaunay三角網(wǎng)格劃分,以剖分后的三角形面片作為視差匹配基元,建立視差模型和能量最小化函數(shù)進(jìn)行初始視差估計(jì)。最后根據(jù)三角形網(wǎng)格共用頂點(diǎn)的特性,對(duì)初始視差進(jìn)行修正,獲得完整的視差圖,經(jīng)重投影矩陣恢復(fù)出場(chǎng)景的三維信息。提出基于離散點(diǎn)云三角剖分的地形三維重建方法,為六足機(jī)器人運(yùn)動(dòng)規(guī)劃提供前方環(huán)境信息。此方法將整個(gè)重建過(guò)程分為三個(gè)步驟:采用空間包圍盒算法對(duì)曲面離散點(diǎn)集進(jìn)行劃分,加速離散點(diǎn)k鄰近點(diǎn)的查找,參數(shù)化點(diǎn)云數(shù)據(jù)后構(gòu)造其切平面,采用基于曲率的方法對(duì)初始點(diǎn)云進(jìn)行數(shù)據(jù)精簡(jiǎn),有效降低了點(diǎn)云拓?fù)浣Y(jié)構(gòu)的復(fù)雜性;點(diǎn)集劃分完成后,區(qū)域內(nèi)根據(jù)異側(cè)不交約束、法向量夾角最大約束、半圓距離約束和最小內(nèi)角最大約束進(jìn)行Delaunay三角剖分;根據(jù)三角形的重?cái)?shù)進(jìn)行各剖分區(qū)域的融合與拼接,實(shí)現(xiàn)最終三角剖分。該算法適用于閉合曲面和非閉合曲面離散點(diǎn)云的三角剖分,剖分后的三角網(wǎng)格均勻、平滑,能較好的體現(xiàn)曲面的細(xì)節(jié)特征。算法執(zhí)行速度快,近萬(wàn)個(gè)離散點(diǎn)云的剖分時(shí)間僅為5.8s。針對(duì)移動(dòng)機(jī)器人僅通過(guò)雙目視覺(jué)來(lái)進(jìn)行定位構(gòu)圖存在精度低和魯棒性差等問(wèn)題,提出一種基于GPU加速的SIFT特征匹配算法,實(shí)現(xiàn)了六足機(jī)器人的同步定位與地圖構(gòu)建。應(yīng)用基于GPU加速的SIFT算法檢測(cè)機(jī)器人運(yùn)動(dòng)前后幀圖像匹配的特征點(diǎn)對(duì),根據(jù)迭代鄰近點(diǎn)算法計(jì)算其旋轉(zhuǎn)與平移,實(shí)現(xiàn)機(jī)器人的位姿估計(jì)。為了防止因場(chǎng)景照明不良或者機(jī)器人運(yùn)動(dòng)不穩(wěn)造成圖像模糊,導(dǎo)致視覺(jué)信息丟失造成視覺(jué)里程計(jì)失靈的問(wèn)題,結(jié)合AHRS傳感器實(shí)現(xiàn)六足機(jī)器人的SLAM。該方法既可以解決單目視覺(jué)利用特殊初始化方法獲取環(huán)境特征點(diǎn)信息不準(zhǔn)確的問(wèn)題,也可以避免單一使用雙目視覺(jué)SLAM恢復(fù)運(yùn)動(dòng)帶來(lái)的計(jì)算量大的缺點(diǎn)。實(shí)驗(yàn)結(jié)果表明,在室內(nèi)環(huán)境下,算法運(yùn)行穩(wěn)定,定位精度高。在前述基于雙目視覺(jué)系統(tǒng)采集地形信息并進(jìn)行地形構(gòu)建的基礎(chǔ)上,依據(jù)地形的幾何信息和六足機(jī)器人自身運(yùn)動(dòng)能力進(jìn)行落足點(diǎn)的初步選取。地形的幾何信息主要考慮到其崎嶇度、高度及可落足區(qū)域的面積。機(jī)器人的運(yùn)動(dòng)能力主要依據(jù)單腿的可達(dá)能力和機(jī)器人位姿的穩(wěn)定性。在可落足點(diǎn)較多的情況下,依據(jù)機(jī)器人的穩(wěn)定裕度及靈活性進(jìn)行落足點(diǎn)的篩選與確定。提出基于障礙物最小凸包曲線的六足機(jī)器人擺動(dòng)相足端軌跡規(guī)劃算法,在降低機(jī)器人的能耗的同時(shí)提高了運(yùn)動(dòng)效率。提出機(jī)器人的位姿調(diào)整算法,通過(guò)調(diào)整機(jī)器人的重心位置、ZMP點(diǎn)至軀干支撐多邊形最大內(nèi)切圓的圓心處,實(shí)現(xiàn)機(jī)器人在平坦地形及崎嶇地形的位姿調(diào)整,保證了六足機(jī)器人下一步運(yùn)動(dòng)的穩(wěn)定性與靈活性利用六足機(jī)器人平臺(tái)HIT-II開(kāi)展綜合實(shí)驗(yàn)研究,設(shè)計(jì)并實(shí)現(xiàn)了六足機(jī)器人系統(tǒng)的控制程序。通過(guò)三組實(shí)驗(yàn)驗(yàn)證了針對(duì)六足機(jī)器人未知環(huán)境下自主行走所提方法和理論的有效性。第一類實(shí)驗(yàn)場(chǎng)景為平坦地形,包含凸起和凹陷障礙。通過(guò)分析環(huán)境感知時(shí)間、感知精度及機(jī)器人的位姿變化,驗(yàn)證了機(jī)器人在該類地形的通過(guò)性能。第二類實(shí)驗(yàn)為柱狀地形,重點(diǎn)驗(yàn)證了落足點(diǎn)選取算法和位姿調(diào)整算法的有效性。第三類實(shí)驗(yàn)場(chǎng)景為仿丘陵地形,通過(guò)立體匹配算法恢復(fù)出地形的點(diǎn)云信息,依據(jù)三角剖分算法重建出機(jī)器人前方環(huán)境地圖。通過(guò)分析機(jī)器人行進(jìn)過(guò)程中的位姿變化,驗(yàn)證立體匹配算法、落足點(diǎn)選取算法及位姿調(diào)整算法的可靠性和有效性。過(guò)實(shí)驗(yàn)對(duì)比發(fā)現(xiàn),地形的復(fù)雜程度影響機(jī)器人的落足點(diǎn)選取及足端軌跡規(guī)劃的執(zhí)行效率,進(jìn)而影響機(jī)器人的行進(jìn)速度。六足機(jī)器人系統(tǒng)的綜合實(shí)驗(yàn)充分驗(yàn)證了所提立體匹配算法、地形構(gòu)建算法、落足點(diǎn)選擇算法、足端軌跡規(guī)劃算法及位姿調(diào)整算法的有效性及可靠性。
[Abstract]:Compared with other wheeled mobile robots, six legged robots have strong terrain adaptation ability and good motion stability. They are playing an important role in many fields, such as military reconnaissance, emergency rescue and disaster relief, interstellar exploration, anti-terrorism blasting, archaeological detection and so on. The ability of six foot robots to cope with the complex environment and to complete the work independently is urgent. The key problem to be solved is to solve the problem of autonomous motion of complex environment of six legged robots as the starting point, focusing on three basic theoretical problems of real-time environment modeling, autonomous positioning and motion planning, and finally taking the typical complex operation environment as demonstration to verify the improvement of autonomous motion under the complex environment of the robot. In order to solve the problem of mutual restriction between matching speed and matching precision in stereo matching, a stereo matching algorithm based on support points is proposed. First, the polar line correction of the original image collected by the camera ensures the corresponding feature points in the matching image on the same pole line. Secondly, the Canny is used. The edge detection operator takes the edge point of the left image of the camera as the stable support point, and uses the divide and conquer method to divide the 2D Delaunay triangular mesh of the support point set. The triangle face after subdivision is used as the parallax matching base, and the parallax model and the energy minimization function are established for the initial parallax estimation. Finally, the triangle mesh is shared by the triangular mesh. The characteristics of the vertex, the correction of the initial parallax, the complete parallax graph, the restoration of the three-dimensional information of the scene through the reprojection matrix. A three-dimensional reconstruction method based on the discrete point cloud triangulation is proposed, which provides the front environment information for the motion planning of the six legged robot. This method divides the whole reconstruction process into three steps: the use of space The bounding box algorithm divides the discrete point set of the surface, accelerates the search of the adjacent points of the discrete point K, constructs its tangent plane after the parameterized point cloud data, and uses the curvature based method to simplify the data of the initial point cloud, effectively reducing the complexity of the topological structure of the point cloud. After the point set is completed, the normal vector is based on the non side constraint and the normal vector. The maximum constraint of the angle, the semicircle distance constraint and the minimum inner corner maximum constraint are Delaunay triangulation, and the final triangulation is realized by the fusion and splicing of the subdivision regions according to the weight of the triangle. The algorithm is suitable for the triangulation of the closed surface and the discrete point cloud of the closed surface. The triangular mesh after the split is uniform, smooth and capable. The algorithm executes the details of the surface better. The algorithm performs fast, and nearly 10000 discrete point clouds are divided by 5.8s. only for the problems of low precision and poor robustness for mobile robots only through binocular vision. A SIFT feature matching algorithm based on GPU acceleration is proposed to realize the synchronization of six legged robots. Using the SIFT algorithm based on GPU acceleration to detect the feature points of the frame image matching before and after the motion of the robot, and calculate its rotation and translation according to the iterative neighborhood point algorithm, and realize the position and pose estimation of the robot. In order to prevent the image blurred caused by the scene illumination or the robot movement instability, the visual information is lost. As a result of the failure of the visual odometer, the implementation of the SLAM. method by combining the AHRS sensor with the AHRS sensor can not only solve the problem of obtaining the inaccurate information of the environmental feature points using the special initialization method in monocular vision, but also avoid the shortcoming of the large amount of computation brought by the single visual SLAM recovery motion. The experimental results show that In the indoor environment, the algorithm runs steadily and the positioning accuracy is high. Based on the previous biocular vision system collecting terrain information and constructing the terrain, the initial selection of the landing point is carried out according to the geometric information of the terrain and the motion ability of the six foot robot. The geometric information of the terrain mainly takes into account its rugged, height and fall. The area of the foot area. The motion ability of the robot is mainly based on the ability of the single leg and the stability of the robot position. In the case of more landing points, the landing point is selected and determined according to the stability margin and flexibility of the robot. The foot track gauge of the wobble phase of the six foot robot based on the minimum convex hull line of the obstacle is put forward. The calculation method improves the motion efficiency while reducing the energy consumption of the robot. The position and posture adjustment algorithm of the robot is proposed. By adjusting the center of gravity of the robot and the ZMP point to the center of the maximum inner tangent circle of the trunk support polygon, the position and posture adjustment of the robot in the flat terrain and rough terrain is realized, and the next step of the six foot robots is ensured. The dynamic stability and flexibility of the six legged robot platform HIT-II are used to carry out comprehensive experimental research. The control program of the six legged robot system is designed and realized. The effectiveness of the method and theory of the autonomous walking for the six foot robot is verified by three groups of experiments. The first class experiment scene is a flat terrain with a convex hull. By analyzing the time of environmental perception, the accuracy of perception and the change of the position and posture of the robot, the performance of the robot in this kind of terrain is verified. The second class experiment is a columnar terrain, and the validity of the algorithm for selecting the landing point and the algorithm of position and posture adjustment is verified. The third kind of actual scene is a hilly terrain, and the stereo matching is calculated by the stereo matching. This method restores the point cloud information of the terrain, and reconstructs the environment map in front of the robot according to the triangulation algorithm. By analyzing the change of the position and posture in the process of robot moving, the stereo matching algorithm, the landing point selection algorithm and the position and attitude adjustment algorithm are reliable and effective. The complexity of the terrain is found to affect the robot. The selection of the landing point and the execution efficiency of the trajectory planning of the foot end affect the moving speed of the robot. The comprehensive experiments of the six foot robot system fully verify the validity and reliability of the proposed stereo matching algorithm, the terrain construction algorithm, the landing point selection algorithm, the foot trajectory planning algorithm and the position and attitude tuning algorithm.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41;TP242

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