摘　　要

工業(yè)機(jī)器人控制系統(tǒng)是機(jī)器人的重要組成部分，主要用于對(duì)操作機(jī)的控制，以完成特定工作任務(wù)。運(yùn)動(dòng)控制器在機(jī)器人控制系統(tǒng)中占核心地位，是機(jī)器人的神經(jīng)中樞。其設(shè)計(jì)好壞決定了機(jī)器人系統(tǒng)的整體行為和整體性能，決定了控制性能的優(yōu)劣，同時(shí)也影響著機(jī)器人使用的方便程度。機(jī)器人運(yùn)動(dòng)學(xué)作為機(jī)器人學(xué)的一個(gè)重要的研究領(lǐng)域，主要研究和解決機(jī)械手臂轉(zhuǎn)向何方的問題，其對(duì)機(jī)器人的控制、機(jī)器人動(dòng)力學(xué)和軌跡規(guī)劃有著深遠(yuǎn)的影響。
針對(duì)傳統(tǒng)求解工業(yè)機(jī)器人逆解問題中存在的不足，給出了一種基于改進(jìn)遺傳算法的機(jī)械手逆解的求解方法。該算法采用了自適應(yīng)的交叉，變異算子，改進(jìn)了排序方法，在保證解的精度的同時(shí)對(duì)解進(jìn)行了合理的優(yōu)化，使求解過程更精確。同時(shí)在求解過程中使用罰函數(shù)法，對(duì)多解問題進(jìn)行優(yōu)化，從而逆解更具有實(shí)用性。選用工業(yè)機(jī)器人PUMA560為對(duì)象進(jìn)行仿真實(shí)驗(yàn)，從算法快速性方面進(jìn)行考慮，滿足了求解過程的實(shí)時(shí)性要求。通過使用MATLAB對(duì)算法進(jìn)行仿真，研究表明，該算法求解精度高，并能有效避免多解。同時(shí)對(duì)比簡(jiǎn)單遺傳算法，該求逆算法具有穩(wěn)定性好，收斂快等優(yōu)點(diǎn)。
針對(duì)現(xiàn)有控制系統(tǒng)的不足，選取OMAP3530和Linux操作系統(tǒng)構(gòu)建整個(gè)工業(yè)機(jī)器人控制系統(tǒng)，突破了傳統(tǒng)工業(yè)機(jī)器人的封閉結(jié)構(gòu)，具有良好的可擴(kuò)展性。在OMAP3530上進(jìn)行編程設(shè)計(jì)并對(duì)該算法進(jìn)行了移植。通過ARM核和DSP核的協(xié)同工作，配合TI官方軟件包Codec Engine，ARM端的應(yīng)用程序調(diào)用DSP端遺傳算法，并最終返回調(diào)用結(jié)果。程序運(yùn)行結(jié)果亦顯示該遺傳算法具有運(yùn)算精度高，運(yùn)行速度快等優(yōu)點(diǎn)；較之普通PC機(jī)，OMAP3530平臺(tái)更小，功耗更低，并且處理速度更快。

關(guān)鍵詞　嵌入式；工業(yè)機(jī)器人；逆解；遺傳算法






































Abstract

Industrial robot control system was an important part of the robot，and was mainly used for manipulator control to accomplish specific tasks. Motion controller accounted for the central position of the robot system，at the same time was the nerve center of the robot. The robot control system design determined the overall performance and the control performance，while also decided the convenience of the use of the robot. Robot kinematics as an important area of the robotics research，mainly solved the question of where the robot turned to. The robot kinematic had far-reaching impact on the robot control，robot dynamics and trajectory planning.
A new method of improved genetic algorithm was proposed to solve the inverse kinematic for manipulator. The algorithm raised an adaptive crossover and mutation operation，also improved the ranking method，with which the problem can be solved accurately and rapidly. The problem of multiple solutions can be optimized by using the penalty function，which can make the inverse kinematic more practical. Then Used the MATLAB for simulation of the genetic algorithm，and the simulation results showed that the algorithm has high accuracy and can effectively avoid multi-solution. Contrasted with the simple genetic algorithm to solve the inverse kinematic，the improved genetic algorithm had good stability，high convergence，etc.
As for the insufficient of the existing controller，selected OMAP3530 and Linux operating system to build the industrial robot control system，which improved the traditional closed structure of industrial robot，also had good scalability. we designed the algorithm and transplanted it on this chip. Programmed on the omap3530，through the cooperation of the ARM core and the DSP core，with the TI official software package Codec Engine，ARM-side applications can successfully call DSP-side genetic algorithm，and return the result of the call. The run results of the genetic algorithm show that the algorithm has high precision，speediness advantage and so on. Compared with an ordinary PC，the OMAP3530 platform is smaller，low-power，and the processing speed is faster.

Keywords　Embeded System；industrial robot；inverse kinematics；genetic algorithm





































目 錄

摘要…………………………………………………………………………………………. I
Abstract……………………………………………………………………………………..III
第1章 緒論 ……………………………………………………………………………… ..1
1.1 課題的研究背景和選題意義 1
1.2 工業(yè)機(jī)器人控制系統(tǒng)的研究概況 3
1.2.1 工業(yè)機(jī)器人國(guó)內(nèi)外研究現(xiàn)狀 3
1.2.2 運(yùn)動(dòng)控制器研究現(xiàn)狀 4
1.3 機(jī)器人逆解的研究概況 5
1.4 課題研究?jī)?nèi)容及主要章節(jié)安排 7
第2章 機(jī)器人運(yùn)動(dòng)學(xué) ……………………………………………………………………..9
2.1 機(jī)器人的數(shù)學(xué)基礎(chǔ) 9
2.1.1 機(jī)器人位姿表示 9
2.1.2 機(jī)器人坐標(biāo)變換 10
2.2 機(jī)器人運(yùn)動(dòng)學(xué) 11
2.2.1 機(jī)器人連桿坐標(biāo)表示 12
2.1.2 機(jī)器人連桿變換矩陣 13
2.1.3 PUMA機(jī)器人運(yùn)動(dòng)學(xué) 14
2.3 PUMA機(jī)器人逆運(yùn)動(dòng)學(xué) 16
2.4 本章小結(jié) 18
第3章 工業(yè)機(jī)器人遺傳算法的逆解分析 ………………………………………………19
3.1 遺傳算法簡(jiǎn)介 19
3.2 遺傳算法的基本理論 20
3.3 機(jī)器人逆解遺傳算法問題描述 21
3.4 改進(jìn)的遺傳算法的機(jī)器人逆解 23
3.5 試驗(yàn)結(jié)果分析 27
3.5.1 仿真..