Democratic multi-robot exploration: New method to compute Particle Swarm Optimizations' global best parameter

Moslah, Oussama; Hachaı̈chi, Yassine; Lahbib, Younes; Kouki, Raed; Tunisie, Himilco; Mami, Abdelkader

doi:10.1109/wscnis.2015.7368299

Cited by 2 publications

(1 citation statement)

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“…The idea was to improve the speed of space exploration by bionic algorithms through multiple robots, such as particle swarm optimization (PSO) and whale optimization algorithm (WOA). 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.…”

Section: Related Workmentioning

confidence: 99%

A Soar-Based Space Exploration Algorithm for Mobile Robots

Luo

Zhou

Fuentes

et al. 2022

Entropy

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Space exploration is a hot topic in the application field of mobile robots. Proposed solutions have included the frontier exploration algorithm, heuristic algorithms, and deep reinforcement learning. However, these methods cannot solve space exploration in time in a dynamic environment. This paper models the space exploration problem of mobile robots based on the decision-making process of the cognitive architecture of Soar, and three space exploration heuristic algorithms (HAs) are further proposed based on the model to improve the exploration speed of the robot. Experiments are carried out based on the Easter environment, and the results show that HAs have improved the exploration speed of the Easter robot at least 2.04 times of the original algorithm in Easter, verifying the effectiveness of the proposed robot space exploration strategy and the corresponding HAs.

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Section: Related Workmentioning

confidence: 99%