本文關(guān)鍵詞：基于協(xié)同顯著性的服務(wù)機(jī)器人空間物體快速定位方法　出處：《機(jī)器人》2017年03期 　論文類型：期刊論文

  更多相關(guān)文章： 服務(wù)機(jī)器人 定位方法 協(xié)同顯著性 圖像間顯著性傳播 流形排序

【摘要】：針對傳統(tǒng)算法模型先檢測、后識別、再定位導(dǎo)致執(zhí)行效率較差的問題,提出了一種基于協(xié)同顯著性檢測的服務(wù)機(jī)器人空間物體快速定位方法.利用RGB-D傳感器獲取N對包含待定位物體的RGB圖像與深度圖像,將待定位物體看作協(xié)同顯著性目標(biāo),在RGB圖像中充分挖掘單幅圖像顯著性傳播機(jī)理,構(gòu)建基于圖像間顯著性傳播和圖像內(nèi)流形排序的兩階段引導(dǎo)協(xié)同顯著性檢測模型,同時排除背景和非協(xié)同顯著性物體,得到協(xié)同顯著性物體區(qū)域的像素坐標(biāo)集合.進(jìn)一步利用RGB圖像與深度圖像的對應(yīng)關(guān)系確定物體質(zhì)心的空間坐標(biāo),實(shí)現(xiàn)對空間物體的快速定位.最后將所提方法在iCoseg標(biāo)準(zhǔn)數(shù)據(jù)庫和經(jīng)手眼標(biāo)定后的服務(wù)機(jī)器人機(jī)械臂抓取平臺上進(jìn)行實(shí)驗(yàn).實(shí)驗(yàn)結(jié)果表明,該方法一致優(yōu)于現(xiàn)有的5種協(xié)同顯著性檢測算法,且滿足抓取系統(tǒng)的實(shí)時性需求,在復(fù)雜背景、多目標(biāo)干擾以及光照變化時具有較高的準(zhǔn)確性和魯棒性.
[Abstract]:The traditional algorithm model is detected first, then identified, and then located, which leads to poor execution efficiency. This paper presents a fast localization method for space objects of service robots based on cooperative salience detection. The RGB-D sensor is used to obtain N pairs of RGB images and depth images containing the objects to be located. The object to be located is regarded as a cooperative significant target, and the significant propagation mechanism of a single image is fully mined in RGB images. A two-stage guided cooperative saliency detection model based on image salience propagation and image manifold sorting was constructed, while background and non-cooperative salience objects were excluded. The pixel coordinate set of the synergetic significant object region is obtained, and the spatial coordinate of the center of mass of the object is determined by using the corresponding relationship between the RGB image and the depth image. Finally, the proposed method is tested on the iCoseg standard database and the manipulator grab platform after the hand-eye calibration. The experimental results show that the proposed method can be used to locate the space objects quickly. The proposed method is superior to the five existing cooperative saliency detection algorithms, and meets the real-time requirements of the grab system. It has high accuracy and robustness in complex background, multi-target interference and illumination change.
【作者單位】： 北京工業(yè)大學(xué)信息學(xué)部;河南科技學(xué)院機(jī)電學(xué)院;
【基金】：北京工業(yè)大學(xué)2017智能制造領(lǐng)域大科研推進(jìn)計(jì)劃(040000546317552) 國家自然科學(xué)基金(61175087)
【分類號】：TP242
【正文快照】： 1引言(Introduction) 制約智能服務(wù)機(jī)器人發(fā)展的關(guān)鍵技術(shù)問題就是如何使機(jī)器人具有人類的智慧,其中對環(huán)境物體準(zhǔn)確、快速的空間感知又是亟待解決的首要問題.近年來,針對不同視覺傳感器的物體檢測、識別、定位技術(shù)一直都是機(jī)器視覺領(lǐng)域的研究熱點(diǎn)[1-3]. 服務(wù)機(jī)器人通過自身搭，

本文編號：1421411