Setting an optimal trajectory for robot using symbolic regression

Abstract

The paper deals with a novelty tool for symbolic regression - Analytic Programming (AP) which is able to solve various problems from the symbolic regression domain including setting an optimal trajectory for robots in space and other industries. In this contribution main principles of AP are described and explained. In second part of the article how AP was used for setting an optimal trajectory for robot according the user requirements is in detail described. An ability to create so called programs, as well as Genetic Programming (GP) or Grammatical Evolution (GE) do, is shown in that part. AP is a superstructure of evolutionary algorithms wich are necessary to run AP. In this contribution SelfOrganizing Migrating Algorithm (SOMA) and Differential Evolution (DE) as two evolutionary algorithms were used to carry simulations out.