本文選題：智能上肢 + 差動繩驅(qū)關(guān)節(jié)��； 參考：《沈陽工業(yè)大學(xué)》2017年碩士論文

【摘要】：智能上肢通常工作于人機交互的環(huán)境中,以安全性為首要要求,同時應(yīng)滿足一定的控制精度和響應(yīng)速度。由于其前端輸入指令多為離散的相對模糊的指令而非準(zhǔn)確的給定運動路徑,智能上肢控制器應(yīng)具有一定的自主安全路徑規(guī)劃能力,這也是其“智能”的體現(xiàn)。因此,智能上肢設(shè)計控制的目標(biāo)是在較為復(fù)雜的日常環(huán)境中,在“向左”、“向右”、“抓取”等離散指令下能夠安全、準(zhǔn)確、迅速且智能地執(zhí)行使用者的運動意圖。文章中智能上肢為自主研發(fā)制作的新型6自由度輕量化智能上肢。首先介紹了在設(shè)計制作方面進行的多種創(chuàng)新,提出了一種差動繩驅(qū)關(guān)節(jié),結(jié)合輕質(zhì)鋁合金加工的結(jié)構(gòu)以滿足智能上肢對于重量、負(fù)載能力以及響應(yīng)速度等各方面的要求。進一步的,根據(jù)其關(guān)節(jié)構(gòu)型,使用改進D-H方法建立了智能上肢數(shù)學(xué)模型。并針對關(guān)節(jié)驅(qū)動的耦合特性,對于包含驅(qū)動器空間-關(guān)節(jié)空間-笛卡爾空間之間相互轉(zhuǎn)換的剛體運動學(xué)與動力學(xué)模型進行了構(gòu)建并提出一種針對其特殊關(guān)節(jié)構(gòu)型的運動學(xué)逆解算法。此部分內(nèi)容是可控變阻抗柔性關(guān)節(jié)(CIVFJ)的硬件基礎(chǔ),運動模型的建立是可控變阻抗柔性關(guān)節(jié)控制及安全路徑規(guī)劃的理論基礎(chǔ)。在此基礎(chǔ)上針對智能上肢可控變阻抗柔性關(guān)節(jié)控制進行了探討。本文實現(xiàn)了一種虛擬可控柔性關(guān)節(jié)并構(gòu)建其動力學(xué)模型,對柔性關(guān)節(jié)領(lǐng)域廣泛使用的控制方法做了較為深入的討論與比較,并最終提出基于Sigmoid函數(shù)的增益自調(diào)節(jié)控制方法,以實現(xiàn)可控變阻抗柔性關(guān)節(jié)能在阻抗系數(shù)與負(fù)載變化的情況下保持理想的位置精度和動態(tài)響應(yīng)特性。這部分研究保證了智能上肢的精度與響應(yīng)速度,同時為以變阻抗柔性關(guān)節(jié)為基礎(chǔ)的被動規(guī)劃方法打下基礎(chǔ)。之后對于安全路徑規(guī)劃的研究,分為主動、被動與主被動結(jié)合三種方式。其中,主動安全路徑規(guī)劃以快速擴展隨機樹(RRT)方法為基礎(chǔ),采用了一種改進RRT*方法,在有視覺監(jiān)督的環(huán)境下,實現(xiàn)障礙環(huán)境中的自主避障。無危險系數(shù)判斷的被動路徑規(guī)劃方法則在視覺監(jiān)督缺失或不可靠的環(huán)境中,通過關(guān)節(jié)柔性的改變,保證運動過程中始終保持較低的潛在傷害。最后本文提出的笛卡爾空間中主被動結(jié)合的規(guī)劃方法,能夠提升智能上肢在動態(tài)復(fù)雜環(huán)境中的安全運行能力,體現(xiàn)出了智能上肢的安全與智能。各章節(jié)中,在Matlab Robotic Toolbox等仿真環(huán)境下,對于智能上肢運動學(xué)、動力學(xué)模型,新提出的逆解算法、變阻抗柔性關(guān)節(jié)控制方法以及主被動安全路徑規(guī)劃方法進行了仿真,并以此為基礎(chǔ)在智能上肢實物上進行了實驗,驗證了其運動模型的合理性以及提出方法的有效性。
[Abstract]:Intelligent upper limbs usually work in the environment of human-computer interaction. Safety is the most important requirement, and the control precision and response speed should be satisfied at the same time. Since most of the front-end input instructions are discrete relatively fuzzy instructions rather than accurate given motion paths, the intelligent upper limb controller should have a certain ability of autonomous safe path planning, which is also the embodiment of its "intelligence". Therefore, the aim of intelligent upper limb design control is to carry out the user's motion intention safely, accurately, quickly and intelligently under discrete instructions such as "left", "right" and "grab" in complex daily environment. In this paper, the intelligent upper limb is a new 6-DOF lightweight intelligent upper limb. In this paper, a variety of innovations in design and manufacture are introduced, and a kind of differential rope drive joint is proposed, which combines the structure of light aluminum alloy machining to meet the requirements of intelligent upper limb in terms of weight, load capacity and response speed. Furthermore, according to its joint configuration, an improved D-H method is used to establish a mathematical model of intelligent upper limb. And aiming at the coupling characteristics of joint drive, The kinematics and dynamics model of rigid body including the transformation between actuator space joint space and Cartesian space is constructed and an inverse kinematics algorithm for its special joint configuration is proposed. This part is the hardware foundation of controllable variable impedance flexible joint (CIVFJ), and the establishment of motion model is the theoretical basis of controllable variable impedance flexible joint control and safe path planning. On this basis, the controllable variable impedance flexible joint control of intelligent upper limb is discussed. In this paper, a virtual controllable flexible joint is implemented and its dynamic model is constructed. The widely used control methods in flexible joint field are discussed and compared in depth. Finally, a gain self-adjusting control method based on Sigmoid function is proposed. In order to realize the controllable variable impedance flexible joint can maintain the ideal position precision and dynamic response characteristic under the condition of the impedance coefficient and the load change. This part of the research ensures the precision and response speed of intelligent upper limb and lays the foundation for passive programming method based on variable impedance flexible joint. After that, the research on safe path planning is divided into three ways: active, passive and passive. The active secure path planning is based on the fast extended random tree (RRT) method, and an improved RRT * method is adopted to realize the autonomous obstacle avoidance in the obstacle environment with visual supervision. In the absence of visual supervision or reliability, the passive path planning method with no risk coefficient can ensure the low potential injury during motion by changing the flexibility of joint. Finally, the planning method of combining active and passive in Cartesian space is proposed in this paper, which can improve the safety operation ability of intelligent upper limb in dynamic and complex environment, and reflect the safety and intelligence of intelligent upper limb. In each chapter, the kinematics and dynamics model of intelligent upper limb, the new inverse solution algorithm, the variable impedance flexible joint control method and the active and passive safe path planning method are simulated under the Matlab Robotic Toolbox simulation environment. On the basis of the experiments, the rationality of the motion model and the validity of the proposed method are verified by experiments on the intelligent upper limb.
【學(xué)位授予單位】：沈陽工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP241

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本文編號：1791418