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基于改進(jìn)適應(yīng)度函數(shù)組合法的機器人逆運動學(xué)求解
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國家自然科學(xué)基金項目(11602082)和湖南省自然科學(xué)基金項目(2018JJ4079)


Solution of Robot Inverse Kinematics with Combination Method of Improved Fitness Function
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    摘要:

    提出基于分離-重構(gòu)方法獲得智能算法的適應(yīng)度函數(shù),并與解析法相結(jié)合求解一般結(jié)構(gòu)多自由度機器人逆運動學(xué),,一般結(jié)構(gòu)滿足至少一組相鄰關(guān)節(jié)軸線交于一點,。利用分離-重構(gòu)的方法構(gòu)建分離-重構(gòu)適應(yīng)度函數(shù),使用智能算法驗證分離-重構(gòu)適應(yīng)度函數(shù),,求解出部分關(guān)節(jié)角,,再結(jié)合解析法求出其余關(guān)節(jié)角。以一般結(jié)構(gòu)的FANUC CRX-10iA型協(xié)作機器人為算例,,使用改進(jìn)的CMA-ES算法驗證分離-重構(gòu)適應(yīng)度函數(shù),,仿真結(jié)果表明,在相同條件下求解的點對點運動中,,單次平均求解時間為0.0040s,,適應(yīng)度函數(shù)值穩(wěn)定在10-7數(shù)量級,且迭代收斂次數(shù)穩(wěn)定在25次左右,;在空間中對兩種連續(xù)軌跡進(jìn)行跟蹤時,單次平均耗時分別為0.0068s和0.0102s,,位置誤差均穩(wěn)定在10-7m數(shù)量級,,且各關(guān)節(jié)運動曲線平滑,提升了多自由度機器人逆運動學(xué)分析的效率和精度,。以REBot-V-6R型六自由度機器人為實驗對象,,基于VC++6.0創(chuàng)建MFC實驗平臺,進(jìn)行連續(xù)的空間軌跡跟蹤實驗,,仿真與實驗結(jié)果驗證了該方法的有效性,。

    Abstract:

    Robot inverse kinematics analysis is the basis of many researches, but the process of multi-degree-of-freedom robot with a general structure inverse kinematics is complicated, and the analytical method may have no solution. Combining the improved fitness function of intelligent algorithm with the analytical method, a method for solving the inverse kinematics of multi-degree-of-freedom robot with a general structure was proposed, which improved the efficiency and accuracy of multi-DOF inverse kinematics analysis. The general structure satisfied at least one set of adjacent joint axes intersect at one point. Using the method of disconnection and reconnection to construct the fitness function of disconnection and reconstruction, and intelligent algorithm was used to verify the fitness function of disconnection and reconstruction and solve some joint angles, and then the analytical method was combined to find the other joint angles. Compared with the fitness function constructed by other methods, this method simplified the process of establishing the fitness function and reduced the algebraic dimensionality of the fitness function. Taking the FANUC CRX-10iA collaborative robot as an example and using the improved CMA-ES algorithm to verify the fitness function of disconnection and reconstruction, the simulation results showed that in the solution of point-to-point inverse kinematics under the same conditions, the single average solution time was 0.0040s, the fitness function value was stable at the order of 10-6, and the iteration convergence times was stable at about 25 times. In order to verify the effectiveness of this method in environments with different levels of complexity, continuous trajectory tracking was performed in two-dimensional and three-dimensional spaces, the average time for a single time was 0.0068s and 0.0102s, respectively, the position error was stable at the level of 10-7m, and the motion curve of each joint was smooth. Taking REBot-V-6R robot of six-DOF as the experimental object, the MFC experimental platform was created based on VC++6.0, and continuous space trajectory tracking experiments were carried out. Simulation and experimental results verified the effectiveness of the method.

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李光,譚薪興,肖帆,易靜,薛晨慷,于權(quán)偉.基于改進(jìn)適應(yīng)度函數(shù)組合法的機器人逆運動學(xué)求解[J].農(nóng)業(yè)機械學(xué)報,2022,53(10):436-445. LI Guang, TAN Xinxing, XIAO Fan, YI Jing, XUE Chenkang, YU Quanwei. Solution of Robot Inverse Kinematics with Combination Method of Improved Fitness Function[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(10):436-445.

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  • 收稿日期:2021-12-17
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  • 在線發(fā)布日期: 2022-02-08
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