Novel Implementation of Multi-Robot Space Exploration Utilizing Coordinated Multi-Robot Exploration and Frequency Modified Whale Optimization Algorithm

Abstract

Multi-robot space exploration involves building a finite map utilizing a cluster of robots in an obstacle cluttered environment. The uncertainties are minimized by assigning tasks among robots and computing the optimum action. Such optimal trajectories are traditionally obtained utilizing deterministic or metaheuristic techniques, with each having peculiar limitations. Recently, limited work with the sub-optimal result has been done utilizing frameworks that utilize a blend of both techniques. This paper proposes a novel framework which involves the integration of deterministic Coordinated Multi-Robot Exploration (CME) and metaheuristic frequency modified Whale Optimization Algorithm (WOA) techniques, to perform search exploration that imitates the predatory behavior of whales. The frequency is dynamically adjusted utilizing a statistical objective function to tune exploitation and exploration operators. The proposed framework involves a) determination of the cost and utility functional values around individual group members utilizing deterministic CME technique, b) search space exploration to optimize and improve the overall solution utilizing frequency modified whale metaheuristic approach. The effectiveness of the proposed Frequency Modified Hybrid Whale Optimization Algorithm (FMH-WOA) is ascertained by training the multi-robotic framework in different complexity environmental conditions. The results efficacy is then demonstrated by comparing the results of the proposed methodology with those achieved from three other contemporary optimization techniques namely CME-WOA, CME-GWO, and CME-SineCosine.

A Soar-Based Space Exploration Algorithm for Mobile Robots

“…In [ 26 ], the authors applied robotic particle swarm optimization (RPSO) to the robot space exploration problem, and the method of calculating the PSO global optimal parameters was utilized to maximize the robot’s exploration area. In [ 27 ], a new framework was proposed that integrates deterministic coordinated multi-robot exploration (CME) and meta-heuristic frequency correction WOA technology to simulate the predating behavior of whales for search and detection. In [ 28 ], researchers proposed a random detection algorithm and applied it to the WOA.…”

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

“…Then, the Whale Optimizer is utilized for evaluating the next step of a robot; refer to Figure 8. References can be found in [250]. A possible algorithm for the methodology mentioned above is presented in Algorithm 1, and a possible literature survey is jotted down in Table 8.…”

Multi-Robot Space Exploration: An Augmented Arithmetic Approach

“…Off recently, Gul et al [27], proposed a novel method for performing search exploration that mimics predatory whale activity by combining deterministic Coordinated Multi-Robot Exploration (CME) and metaheuristic frequency adjusted Whale Optimization Algorithm (WOA) techniques. To tune exploitation and exploration operators, the frequency parameter was dynamically modified using an analytical, statistical function.…”

“…These problems are inherently nonlinear in nature, and usually subjected to various path/terminal constraints [12]. The recent trend is to use bio-inspired optimizing algorithms, which offer a promising approach to solve problems which could not be handled efficiently through conventional optimization algorithms [27].…”