Orientation angle based online motion control of an Aldebaran NAO humanoid robot in V-REP software environment using novel sunflower optimization (SFO) algorithm

This paper presents the novel Sunflower Optimization (SFO) algorithm based online motion and orientation planner for an Aldebaran NAO humanoid robot (NAO robot) in the Virtual Robot Experimentation Platform (V-REP) software environment. For this purpose, we have taken the rear-time sonar sensors data of obstacles as inputs and chosen the complete orientation angle as an output of the NAO robot to make the objective function for the SFO algorithm. The designed objective function controls the orientation angle of the NAO robot during navigation and obstacle avoidance. Next, the programming of the SFO algorithm and forward kinematic equations have been written in MATLAB scripts. Through the application programming interface functions, these scripts give the orientation angle control command to the NAO robot in the V-REP software environment between obstacles. The two-dimensional (2D) and three-dimensional (3D) experimental results of the proposed SFO algorithm-controlled NAO robot are performed in the MATLAB and V-REP software environments. A comparative analysis between the SFO algorithm and the Adaptive Particle Swarm Optimization algorithm has also been done to show the effectiveness and efficiency of the proposed algorithm.