Study and Analysis of Mobile and Humanoid Robots using Intelligent Optimization Techniques

Abstract

In the current research work, different intelligent algorithms have been analyzed for navigation of robots in cluttered environments consisting of various obstacles. Here, several papers have been reviewed and analyzed based on different artificial intelligence techniques. Based on the research gap available with the existing literature, the objectives of the current research is set as design and implementation of several intelligent algorithms as navigational models in both mobile and humanoid robots. The algorithms such as Cell decomposition, Neural Network, Invasive weed optimization and a hybrid technology named as Neuro-IWO are applied on the robots. The working of the navigational controllers is tested on simulation platforms and the navigational patterns obtained from the simulation platforms are validated through real-time set-ups developed under laboratory conditions. Finally, the results obtained from both the simulation and experimental platforms are compared against each other and are found to be in good agreement with minimal percentage of errors.