Single and multiple humanoid path planning using Hill valley approach applied to gravitational drift in Gravitational search algorithm

Abstract

AbstractIn this paper, the Hill Valley (HV) approach is applied to the drifting masses or agents in the basic Gravitational Search Algorithm (GSA) for the path planning of humanoid robots. The drift in lighter masses toward the heavier mass creates a localized area, where the probability of obtaining a globally optimal solution is very high. So, the present work is focused on exploiting the area to tackle local optima and provide the best steering angle for the humanoids to navigate. The HV approach is applied to the basic GSA model, at the later stages, to improve the overall computational time and cost. The robustness of the proposed controller was tested in both simulation and experimental environments and compared with the previous research. The results obtained from the proposed controller showed a significant improvement in the overall path length and time taken. Path smoothness was also given equal importance during path planning to ensure stability. The multi-robot navigational scheme was performed using the Dining Philosopher’s model to avoid dynamic collision among the humanoids. The percentage deviation in the results was within the acceptable limits. To further check the effectiveness of the proposed technique, the proposed approach was compared with the vision-based navigation in danger space.