Collision Avoidance for a Selective Compliance Assembly Robot Arm Manipulator Using Topological Path Planning

被引:2
|
作者
Batista, Josias G. [1 ]
Ramalho, Geraldo L. B. [1 ]
Torres, Marcelo A. [1 ]
Oliveira, Anderson L. [1 ]
Ferreira, Daniel S. [2 ]
机构
[1] Fed Inst Educ Sci & Technol Ceara IFCE, Dept Ind, Automat & Ind Networks Lab, Campus Fortaleza, BR-60040215 Fortaleza, CE, Brazil
[2] Fed Inst Educ Sci & Technol Ceara IFCE, Dept Comp Sci, Campus Maracanau, BR-61939140 Maracanaue, CE, Brazil
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 21期
关键词
path planning; collision avoidance; topological path; collaborative robotics; PROBABILISTIC ROADMAP;
D O I
10.3390/app132111642
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Industrial applications with robotic manipulators have grown and made production systems increasingly efficient. However, there are still some limitations that can delay production, causing losses. Several factors, such as accidents and collisions of manipulator robots with operators and other machines, can cause unforeseen stops. Thus, this work aims to develop a trajectory planning method to avoid collisions applied to a selective compliance assembly robot arm (SCARA) robotic manipulator in the context of collaborative robotics. The main contribution of this paper is a path planning method based on mathematical morphology, named topological path planning (TPP). Through some evaluation metrics such as the number of path points, computing time, distance, standard deviation of the joint acceleration, and maximum acceleration rate along the path, we show that TPP is a collision-free, deterministic, and predictable route planning. In our experiments, our proposal presented better results for applications in industrial robotic manipulators when compared to the probabilistic roadmap method (PRM) and TPP*, a particular case of TPP that is similar to the generalized Voronoi diagram (GVD).
引用
收藏
页数:19
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