Comparing the efficiency of five algorithms applied to path planning for industrial robots
Purpose The purpose of this paper is to compare the quality and efficiency of five methods for solving the path planning problem of industrial robots in complex environments. Design/methodology/approach In total, five methods are presented for solving the path planning problem and certain working pa...
| Authors: | , , , |
|---|---|
| Format: | article |
| Publication Date: | 2012 |
| Country: | España |
| Institution: | Universitat Politècnica de València (UPV) |
| Repository: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Language: | English |
| OAI Identifier: | oai:riunet.upv.es:10251/77972 |
| Online Access: | https://riunet.upv.es/handle/10251/77972 |
| Access Level: | Open access |
| Keyword: | Programming and algorithm theory Robots Kinematics Industrial robots Path planning Collision avoidance Off-line programming Multi-arms robot INGENIERIA MECANICA |
| Summary: | Purpose The purpose of this paper is to compare the quality and efficiency of five methods for solving the path planning problem of industrial robots in complex environments. Design/methodology/approach In total, five methods are presented for solving the path planning problem and certain working parameters have been monitored using each method. These working parameters are the distance travelled by the robot and the computational time needed to find a solution. A comparison of results has been analyzed. Findings After this study, it could be easy to know which of the proposed methods is most suitable for application in each case, depending on the parameter the user wants to optimize. The findings have been summarized in the conclusion section. Research limitations/implications The five techniques which have been developed yield good results in general. Practical implications The algorithms introduced are able to solve the path planning problem for any industrial robot working with obstacles. Social implications The path planning algorithms help robots perform their tasks in a more efficient way because the path followed has been optimized and therefore they help human beings work together with the robots in order to obtain the best results from them. Originality/value The paper shows which algorithm offers the best results, depending on the example the user has to solve and the parameter to be optimized. |
|---|