Evolutionary algorithms in kinematic design of robotic systems

This paper proposes an Adaptative Multi-Chromosome Evolutionary Algorithm (AMEA) to perform task based design of modular robotic systems. The kine-matic design is optimized by the AMEA which uses both binary and real encoding (for kinematic and con-guration parameters). In the problem considered for illustration, the robotic system consists in a mobile base and a manipulator arm which may be built with serially assembled link and joint modules. The manip-ulator has to reach a predeened set of goal frames in a 3D cluttered environment. Its design is evaluated with geometric and kinematic performance measures. Optimization results for a 3D task are given and compared with a Simple Genetic Algorithm. They clearly show the superiority of the Multi-Chromosome representation and adaptive operators in term of computing time and criteria optimization performance.