Multi-Objective Optimization of Snake Robot in Serpentine Locomotion

Abstract

This paper presents multi-objective optimization for a snake robot with serpentine locomotion. Genetic algorithm (GA) is used to achieve two objectives: minimizing the total travelling time and minimizing the total energy consumption. The effect of initial values of winding angle and acceleration on energy consumption and average speed is depicted. The simulation results show a periodic pattern of the joint torques when the robot maintains a serpenoid curve during travel. Moreover, a Pareto-optimal front was generated for optimal solutions of both of the objectives, while the weighted sum method was used for selecting the best solution. Finally, the simulation results were verified experimentally on an eight-link snake robot considering the limitations of the servomotors used in the experiment. The experimental results with the winding angle of 30° was found as the optimum winding angle that can achieve both objectives of minimizing the energy consumption and the travelling time. ABSTRAK: Kajian ini berkenaan pelbagai-objektif optimum bagi robot ular dengan gerakan serpentin. Algoritma genetik (GA) diguna bagi mencapai dua objektif ini iaitu mengurangkan jumlah masa gerakan dan guna tenaga. Gambaran kesan awal nilai sudut belitan dan pecutan pada guna tenaga dan purata kelajuan dihasilkan. Dapatan simulasi menunjukkan corak berkala tork sendi yang tetap terhasil semasa robot ini berkeadaan lengkung serpenoid ketika bergerak. Tambahan, Pareto-optimal berdepan terhasil bagi solusi optimum pada kedua-dua objektif, sementara kaedah berat campuran digunakan bagi menentukan solusi terbaik. Akhirnya, dapatan simulasi disahkan secara eksperimen pada robot ular lapan-bahagian dengan menimbangkan kekurangan servomotor yang digunakan dalam eksperimen. Dapatan eksperimen menunjukkan sudut belitan 30° adalah sudut belitan optimum bagi kedua-dua objektif iaitu mengurangkan tenaga dan masa gerakan.

Optimal Distribution Network Reconfiguration Using Multi-Objective Cuckoo Search Algorithm

“…On the other hand, multi-objective optimization is a technique when two or more objectives are considered simultaneously to achieve the most desired outcome. This technique is used in many fields like economics, logistics, management, science, and engineering [13]. Unlike single-objective, this approach does not require a weight factor in the objective function.…”