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Multi-Objective Whale Optimization Algorithm for Balance Recovery of a Humanoid Robot

Kittisak Sanprasit and Pramin Artrit
Dept. Electrical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand

Abstract— In the near future, the humanoid robot has been expected to associate and work with a human. There is a chance that it has been hit from an external force and the robot cannot keep its balance. Thus, the robot might falls to human causing casualty or if it falls down to the ground the damage could cause ultimately to itself. For this reason, the humanoid must have balance recovering processes for protecting itself from the external force to prevent such damage. Therefore, this research proposes an optimal path design for a stand-balancing humanoid robot. The experiment simulates this situation using a force 1.11N hits to the humanoid (Bioloid Premium Type A) robot. This commercial humanoid robot has 18 Degree of Freedoms (DOFs). With this complexity of DOFs, the mathematical model and joints control strategies are investigated to restore robot balancing. Six strategies are chosen to implement in this work; 1) ankle strategy, 2) knee strategy, 3) ankle and knee strategy, 4) ankle and hip strategy, 5) ankle knee and hip strategy, and 6) whole body (ankle, knee, hip, arms) strategy using Multi-objective Whale optimization algorithm (MOWOA) together with non-dominated solution and decision making by weighted product method. Three objective functions are employed; 1) a minimal orbital energy, 2) a minimal error of phase portrait, and 3) a minimal jerk. The results have shown that the ankle strategy gives the best result based on decision making by the weighted product method.

 
Index Terms— Humanoid Robot, MOWOA, weighted product method, Pareto front, Balancing, objective functions

Cite: Kittisak Sanprasit and Pramin Artrit, "Multi-Objective Whale Optimization Algorithm for Balance Recovery of a Humanoid Robot," International Journal of Mechanical Engineering and Robotics Research, Vol. 9, No. 6, pp. 882-893, June 2020. DOI: 10.18178/ijmerr.9.6.882-893

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.