本文關(guān)鍵詞： 空間機器人控制技術(shù) 體感技術(shù) 人機交互 手勢識別 圖像處理　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：依托空間機器人控制技術(shù)的高速發(fā)展,宇航員和空間機器人的交互活動愈發(fā)頻繁和普遍。機器視覺領(lǐng)域中的手勢識別方法研究對于實現(xiàn)新型人機交互方式將起到極為關(guān)鍵的作用。本論文的研究目的是期望建立一種航天員通過手勢操縱空間機器人或飛行器全向運動并輔助完成空間任務(wù)的新型控制系統(tǒng),這對于我國未來空間應(yīng)用技術(shù)的發(fā)展有很高的研究價值和發(fā)展前景。本論文的主要研究內(nèi)容是基于深感攝像機實現(xiàn)了人體靜態(tài)手勢和動態(tài)手勢的動作識別。此外,對文中的手勢識別控制系統(tǒng)在空間站服務(wù)型機器人上的應(yīng)用做了可行性分析。最后,設(shè)計了一套操作者通過手勢動作控制輪式機器人全向運動的硬件系統(tǒng),從而完成了這種新型無接觸式的手勢控制方式的方法驗證。本論文中靜態(tài)手勢識別的研究是使用本文提出的基于膚色檢測和深度閾值相結(jié)合的方法進行圖像中手部區(qū)域的分割和提取。然后,通過對圖像降噪處理和細化處理獲得手部骨架圖并通過文中提出的基于手骨架圖的特征點提取方法進行手部關(guān)鍵節(jié)點的識別和提取。最后,通過建立靜態(tài)手勢三維模型實現(xiàn)了具有更高準(zhǔn)確性和快速性的靜態(tài)手勢識別。文中動態(tài)手勢識別的研究是基于改進的動態(tài)時間規(guī)整方法通過將采集到的手勢動作運動軌跡序列與預(yù)先建立的標(biāo)準(zhǔn)動作模板庫進行對比和匹配。實驗測試結(jié)果表明,文中改進后的動態(tài)時間規(guī)整方法實現(xiàn)了具有更高準(zhǔn)確性和快速性的動態(tài)手勢識別。此外,本文把手勢控制應(yīng)用到機器人控制系統(tǒng)中,實現(xiàn)了一種新型的機器人控制方式。同時,對于宇航員手勢控制空間站服務(wù)型機器人做了可行性和可用性的仿真分析與驗證。
[Abstract]:Relying on the rapid development of space robot control technology, The interaction between astronauts and space robots is becoming more and more frequent and common. The research of gesture recognition in the field of machine vision will play a crucial role in the realization of a new type of human-computer interaction. The purpose of this paper is to. Desiring to establish a new type of control system in which astronauts use gestures to manipulate the omnidirectional motion of space robots or aircraft and to assist in the completion of space missions, This will be of great value and prospect for the future development of space application technology in our country. The main research content of this thesis is to realize the motion recognition of human body static and dynamic gestures based on deep sense camera. The feasibility of the application of the gesture recognition control system in the space station service robot is analyzed. Finally, a hardware system is designed to control the omnidirectional motion of the wheeled robot by hand gesture. In this paper, the method of static gesture recognition is based on the combination of skin color detection and depth threshold. The segmentation and extraction of the region. Then, The hand skeleton map is obtained by image denoising and thinning processing, and the hand key nodes are identified and extracted by the method of feature point extraction based on hand skeleton image proposed in this paper. The static gesture recognition with higher accuracy and rapidity is realized by establishing 3D static gesture model. The research of dynamic gesture recognition in this paper is based on the improved dynamic time regularization method. The motion trajectory sequence is compared and matched with the pre-established standard action template library. The experimental results show that, The improved dynamic time warping method realizes the dynamic gesture recognition with higher accuracy and rapidity. In addition, this paper applies the gesture control to the robot control system to realize a new robot control mode. Simulation analysis and validation of the feasibility and availability of the space station service robot with astronaut gesture control are carried out.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP242;V441

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