Solving Inverse Kinematics with Vector Evaluated Particle Swarm Optimization

被引：0
|
作者：
Riekert, Zuhnja [1 ]
Helbig, Marde [1 ]
机构：
[1] Univ Pretoria, Pretoria, South Africa
来源：
ADVANCES IN SWARM INTELLIGENCE, ICSI 2017, PT I | 2017年 / 10385卷
关键词：
D O I：
10.1007/978-3-319-61824-1_25
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Inverse kinematics (IK) is an optimization problem solving the path or trajectory a multi-jointed body should take for an extremity to reach a specified target location. When also considering the flow of movement, IK becomes a multi-objective optimization problem (MOP). This study proposes the use of the vector evaluated particle swarm optimization (VEPSO) algorithm to solve IK. A 3D character arm, with 7 degrees of freedom, is used during experimentation. VEPSO's results are compared to single-objective optimizers, as well as an optimizer that uses weighted aggregation to solve MOPs. Results show that the weighted aggregation approach can outperform IK-VEPSO if the correct weight combination (that is problem dependent) has been selected. However, IK-VEPSO produces a set of possible solutions.
引用
收藏
页码：225 / 237
页数：13
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