Optimization of route planning for the mobile robot using a hybrid Neuro-IWO technique

Using route planning techniques, a robot can easily travel from a starting point to a destination point without colliding with any substances in the given workspace. Also, the Route planning technique is used to shorten the path length of any robot movement. This paper presents a hybrid route planning algorithm, Neuro-IWO, based on a combination of Neural Network and Invasive Weed Optimization (IWO). The proposed algorithm combines the Neural Network (NN) and the IWO to determine the most optimized route between the beginning and destination points. Experiments were conducted on both NN and Neuro-IWO algorithms. From the results, it has been observed that Neuro-IWO achieves good accuracy and is the shortest route compared to NN. The NN gives a deviation of below 6%, at the same time, Neuro-IWO gives a deviation of below 5%.