【摘要】：隨著機(jī)器人技術(shù)的快速發(fā)展,機(jī)器人已經(jīng)開始走出工業(yè)生產(chǎn)線,走向千家萬(wàn)戶,有望很快服務(wù)大眾。作為一個(gè)典型的非線性復(fù)雜系統(tǒng)和多學(xué)科交叉的綜合集成系統(tǒng),服務(wù)機(jī)器人的研制涉及內(nèi)容廣,面臨挑戰(zhàn)大。如何有效的提高服務(wù)機(jī)器人的性能,尤其是提高其柔性化水平以滿足與人交互的各項(xiàng)服務(wù)任務(wù)的需求,成為一個(gè)富有挑戰(zhàn)性的重大課題。本文以作者在攻讀博士學(xué)位期間參與的可佳機(jī)器人項(xiàng)目為基礎(chǔ),介紹了服務(wù)機(jī)器人的基本設(shè)計(jì)和柔性化思想,以及軟體執(zhí)行器、柔性感知規(guī)劃等若干前沿技術(shù)。第一部分論述服務(wù)機(jī)器人面臨的設(shè)計(jì)上的挑戰(zhàn)-提升交互體驗(yàn)、降低系統(tǒng)復(fù)雜度和提高柔性化水平等。本文以可佳服務(wù)機(jī)器人為例,介紹作者為解決這些挑戰(zhàn),在機(jī)器人設(shè)計(jì)方面采用的一些方法,如功能替代、融合設(shè)計(jì)和自由度分布優(yōu)化等。機(jī)械系統(tǒng)是機(jī)器人產(chǎn)生行為的基礎(chǔ),對(duì)機(jī)器人的執(zhí)行任務(wù)范疇和執(zhí)行效果具有重大的影響。合理的機(jī)械系統(tǒng)應(yīng)該綜合考慮任務(wù)范圍和操作類型以布置自由度并設(shè)計(jì)不同種類的運(yùn)動(dòng)機(jī)構(gòu),同時(shí)應(yīng)該考慮降低控制難度,盡量減少因硬件結(jié)構(gòu)產(chǎn)生的運(yùn)動(dòng)學(xué)復(fù)雜計(jì)算求解。同時(shí),機(jī)器人的運(yùn)動(dòng)關(guān)節(jié)較多,進(jìn)行自由度分布的優(yōu)化可以大大增強(qiáng)系統(tǒng)的柔性和魯棒性。第二部分論述了服務(wù)機(jī)器人的執(zhí)行系統(tǒng)面臨的挑戰(zhàn)-如何增強(qiáng)機(jī)器人的柔性化,提高其安全性。本文介紹了一種有望徹底解決機(jī)器人柔性化不足的前沿技術(shù)-軟體機(jī)器人技術(shù)。相對(duì)于傳統(tǒng)硬質(zhì)機(jī)器人而言,軟體機(jī)器人具有天然的柔性和安全性,更加適合服務(wù)機(jī)器人與人交互的特點(diǎn)。本文從仿生學(xué)觀點(diǎn)出發(fā),提出了一種蜂巢式氣動(dòng)仿生機(jī)器人,并對(duì)其運(yùn)動(dòng)性能進(jìn)行了初步的分析。實(shí)驗(yàn)證明此構(gòu)型的軟體機(jī)器人在伸縮率和彎曲率方面的性能十分優(yōu)異,并且還具備自變剛度的特性,是一項(xiàng)非常有前景的機(jī)器人基礎(chǔ)技術(shù)。第三部分論述了服務(wù)機(jī)器人在感知-規(guī)劃方面的挑戰(zhàn)。智能服務(wù)機(jī)器人在工作空間內(nèi)需要利用自身傳感器進(jìn)行環(huán)境信息的感知并進(jìn)行合理的行為規(guī)劃,但由于機(jī)載設(shè)備性能限制,機(jī)器人得到的環(huán)境信息極為有限,限制了其感知規(guī)劃能力的提升。近年來,隨著智能物聯(lián)網(wǎng)、智能家居、普適計(jì)算的興起,利用外部傳感器信息和知識(shí)對(duì)機(jī)器人的感知能力進(jìn)行增強(qiáng)成為一個(gè)研究前沿。本文提出利用柔性傳感器進(jìn)行外部感知,并提出一種規(guī)劃技術(shù)來對(duì)智能機(jī)器人的感知規(guī)劃能力進(jìn)行進(jìn)一步的提升。本文的主要貢獻(xiàn)和創(chuàng)新之處如下：首先,本文基于可佳服務(wù)機(jī)器人,論述了服務(wù)機(jī)器人功能設(shè)計(jì)要素,介紹了其曳引對(duì)重升降結(jié)構(gòu)、模塊化手臂等獨(dú)特設(shè)計(jì)。同時(shí)提出一種新的柔性責(zé)任矩陣技術(shù),基于運(yùn)動(dòng)關(guān)節(jié)與任務(wù)空間的逆微分關(guān)系,將關(guān)節(jié)空間補(bǔ)償映射為末端執(zhí)行空間誤差補(bǔ)償,通過關(guān)節(jié)空間補(bǔ)償以較小的剛度損失增加了執(zhí)行器在目標(biāo)維度上的補(bǔ)償度。其次,本文基于仿生學(xué)觀點(diǎn),利用柔性蜂巢結(jié)構(gòu)模擬植物細(xì)胞壁、微型氣動(dòng)單元模擬細(xì)胞膜離子泵,提出了一種新的仿生軟體執(zhí)行器-蜂巢氣動(dòng)網(wǎng)絡(luò)。本文研究了該執(zhí)行器的靜力學(xué)模型,建立了其超冗余度并聯(lián)機(jī)構(gòu)運(yùn)動(dòng)學(xué)模型,以及基于彈簧-質(zhì)點(diǎn)系的動(dòng)力學(xué)仿真模型。同時(shí),利用彈性金屬和微型氣袋制造了原型機(jī)并進(jìn)行測(cè)試,實(shí)驗(yàn)表明該種軟體執(zhí)行器伸縮率可達(dá)800%,具備同時(shí)進(jìn)行三維彎曲和伸縮能力,對(duì)目標(biāo)物體可進(jìn)行面貼合,性能較先前軟體執(zhí)行器有了大幅提高。最后,論文研究了利用柔性傳感器進(jìn)一步提升其環(huán)境感知規(guī)劃能力,提出一種采用智能織物作為外部感知器的柔性感知-規(guī)劃技術(shù),并著重研究了環(huán)境傳感器下的算法優(yōu)化。通過分析隨機(jī)搜索樹在凸空間內(nèi)采樣區(qū)域和碰撞事件的關(guān)系,提出通過碰撞檢測(cè)避免采樣區(qū)域超前導(dǎo)致搜索效率下降問題,并根據(jù)碰撞信息進(jìn)行指數(shù)級(jí)的采樣區(qū)域調(diào)整,有效的加速了搜索樹向目標(biāo)區(qū)域收斂的速度。實(shí)驗(yàn)證明,在計(jì)算機(jī)隨機(jī)生成的障礙物地圖上,該算法較原RRT算法有一個(gè)數(shù)量級(jí)的速度提升,達(dá)到了感知規(guī)劃的實(shí)時(shí)要求。
[Abstract]:With the rapid development of the technology of the robot, the robot has begun to walk out of the industrial production line, to a million households, and is expected to serve the public soon. As a typical non-linear complex system and a multi-subject integrated integrated system, the development of the service robot involves a wide range of content and a great challenge. How to effectively improve the performance of the service robot, especially to improve the flexibility level to meet the demands of various service tasks with people, becomes a challenging and important subject. The paper introduces the basic design and flexibility of the service robot, as well as a number of front-edge technologies such as soft-actuator and flexible sensing planning, based on the good-robot project involved in the study of the doctor's degree. The first part discusses the design challenges facing the service robot-enhancing the interactive experience, reducing the complexity of the system and improving the flexibility level. This paper takes a good service robot as an example, and introduces some methods to solve these challenges, such as function substitution, fusion design and freedom distribution optimization. The mechanical system is the basis of the robot's behavior, and has a great influence on the execution task category and the performance of the robot. The reasonable mechanical system should take into account the task range and the operation type to arrange the degree of freedom and design different kinds of motion mechanism. At the same time, the control difficulty should be reduced, and the complex calculation of the kinematics due to the hardware structure should be minimized. At the same time, the motion joint of the robot is more, and the optimization of the degree of freedom distribution can greatly enhance the flexibility and the robustness of the system. The second part discusses the challenge of the implementation system of the service robot-how to enhance the flexibility of the robot and improve the security. This paper introduces a technology-soft-robot technology which is expected to completely solve the defects of the robot's flexibility. Compared with the traditional rigid robot, the soft robot has the characteristics of natural flexibility and safety, and is more suitable for the interaction of the service robot and the human. In this paper, a kind of honeycomb-type pneumatic bionic robot is put forward from the view of bionics, and the motion performance of the robot is analyzed. The experimental results show that the soft-robot with this configuration has excellent performance in the aspects of extension rate and bending rate, and also has the characteristics of self-variable stiffness, which is a very promising base technology of the robot. The third part discusses the challenge of the service robot in the sense-planning. In the working space, the intelligent service robot needs to use its own sensor to sense the environment information and conduct reasonable behavior planning, but due to the limitation of the performance of the airborne equipment, the environment information obtained by the robot is very limited, and the improvement of its perception planning ability is limited. In recent years, with the rise of the intelligent Internet of things, the intelligent home and the pervasive computing, the sensing ability of the robot is enhanced by using the external sensor information and knowledge. In this paper, an external perception is made by using a flexible sensor, and a planning technique is proposed to further improve the perception planning capability of the intelligent robot. The main contribution and innovation of this paper are as follows: Firstly, based on the good service robot, this paper discusses the design elements of the service robot, and introduces the unique design of the lifting structure, the modular arm and so on. At the same time, a new flexible liability matrix technique is proposed, based on the inverse differential relation between the motion joint and the task space, the joint space compensation is mapped to the end execution space error compensation, and the compensation degree of the actuator in the target dimension is increased by the joint space compensation with a small stiffness loss. Secondly, based on the bionics, this paper presents a new bionic soft-actuator-cellular pneumatic network by using the flexible honeycomb structure to simulate the cell wall and the micro-pneumatic unit to simulate the cell membrane ion pump. In this paper, the static model of the actuator is studied, the kinematic model of the super-redundant parallel mechanism is established, and the dynamic simulation model based on the spring-mass point system is established. At the same time, the prototype is manufactured by the elastic metal and the micro air bag, and the test is carried out. The experiment shows that the expansion rate of the soft actuator can reach 800%, the three-dimensional bending and the expansion capability can be simultaneously carried out, the surface bonding of the target object can be carried out, and the performance is greatly improved compared with the prior software actuator. In the end, the paper studies the ability of the flexible sensor to further improve its environment-aware planning, and puts forward a flexible sensing-planning technique using the intelligent fabric as an external sensor, and focuses on the optimization of the algorithm under the environment sensor. By analyzing the relation between the sampling region and the collision event in the convex space of the random search tree, the problem of reducing the search efficiency by collision detection is proposed, and the sampling region of the exponential stage is adjusted according to the collision information, The speed of the search tree to converge towards the target region is effectively accelerated. The experimental results show that the algorithm has an order of magnitude higher than that of the original RRT algorithm, and the real-time requirement of the sensing planning is achieved.
【學(xué)位授予單位】：中國(guó)科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP242

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