English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Grasp planning is one of the most interesting subjects of object manipulation tasks in robotics and the development of grasp methods would be affected the robot performance. One of the most important subjects which is discussed in grasp planning, especially in industrial applications, is optimal grasp planning and finding the best grasping point. So it is important to find the best grasping point that the manipulator contact with object. In this paper, the MAG performance index, which is designed for object manipulation tasks, would be used for two different types of objects which are manipulated in the predefined path. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) methods would be used to maximize this index and find the best grasping point and finally compared with each other. The results show that in faster object manipulation tasks, the GA method is more suitable than PSO method. Since in accurate object manipulation tasks, the PSO method is preferred to GA method.

FINDING THE BEST GRASPING POINT IN OBJECT MANIPULATION TASKS - A Comparison between GA and PSO Methods