Locomotion of Bioinspired Underwater Snake Robots Using Metaheuristic Algorithm

Snake Robots (SR) have been successfully deployed and proved to attain bio-inspired solutions owing to its capability to move in harsh environments, a characteristic not found in other kinds of robots (like wheeled or legged robots). Underwater Snake Robots (USR) establish a bioinspired solution in the domain of underwater robotics. It is a key challenge to increase the motion efficiency in underwater robots, with respect to forwarding speed, by enhancing the locomotion method. At the same time, energy efficiency is also considered as a crucial issue for long-term automation of the systems. In this aspect, the current research paper concentrates on the design of effectual Locomotion of Bioinspired Underwater Snake Robots using Metaheuristic Algorithm (LBIUSR-MA). The proposed LBIUSR-MA technique derives a bi-objective optimization problem to maximize the Forward Velocity (FV) and minimize the Average Power Consumption (APC). LBIUSR-MA technique involves the design of Manta Ray Foraging Optimization (MRFO) technique and derives two objective functions to resolve the optimization issue. In addition to these, effective weighted sum technique is also used for the integration of two objective functions. Moreover, the objective functions are required to be assessed for varying gait variables so as to inspect the performance of locomotion. A detailed set of simulation analyses was conducted and the experimental results demonstrate that the developed LBIUSR-MA method achieved a low Average Power Consumption (APC) value of 80. under δ value of 50. The proposed model accomplished the minimum PAC and maximum FV of USR in an effective manner.