Path planning optimization of six-degree-of-freedom robotic manipulators using evolutionary algorithms

被引:53
作者
Segota, Sandi Baressi [1 ]
Andelic, Nikola [1 ]
Lorencin, Ivan [1 ]
Saga, Milan [2 ]
Car, Zlatan [1 ]
机构
[1] Univ Rijeka, Fac Engn, Vukovarska 58, Rijeka 51000, Croatia
[2] Univ Zilina, Fac Mech Engn, Zilina, Slovakia
关键词
Artificial intelligence; cooperating robotic manipulators; differential evolution; genetic algorithm; robot trajectory planning; simulated annealing; POPULATION GENETIC ALGORITHM; GENERATION; ALLOCATION; SWARMS; TIME;
D O I
10.1177/1729881420908076
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Lowering joint torques of a robotic manipulator enables lowering the energy it uses as well as increase in the longevity of the robotic manipulator. This article proposes the use of evolutionary computation algorithms for optimizing the paths of the robotic manipulator with the goal of lowering the joint torques. The robotic manipulator used for optimization is modelled after a realistic six-degree-of-freedom robotic manipulator. Two cases are observed and these are a single robotic manipulator carrying a weight in a point-to-point trajectory and two robotic manipulators cooperating and moving the same weight along a calculated point-to-point trajectory. The article describes the process used for determining the kinematic properties using Denavit-Hartenberg method and the dynamic equations of the robotic manipulator using Lagrange-Euler and Newton-Euler algorithms. Then, the description of used artificial intelligence optimization algorithms is given - genetic algorithm using random and average recombination, simulated annealing using linear and geometric cooling strategy and differential evolution. The methods are compared and the results show that the genetic algorithm provides best results in regard to torque minimization, with differential evolution also providing comparatively good results and simulated annealing giving the comparatively weakest results while providing smoother torque curves.
引用
收藏
页数:16
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