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.