Home /Research /PSO-Based Nature-Inspired Mechanisms for Robots during Smart Decision-Making for Industry 4.0
SWARM

PSO-Based Nature-Inspired Mechanisms for Robots during Smart Decision-Making for Industry 4.0

Harinder Singh, Veera Talukdar, Huma Khan, Dharmesh Dhabliya, Rohit Anand, Abhra Pratip Ray, Sanjiv Jain

Year
2023
Citations
3

Abstract

The focus of this study is on the usage of particle swarm optimization (PSO) for smart decision-making by robotics. Data-driven decisions across the value chain enable the increased efficiency and productivity that define Industry 4.0's smart factories and ubiquitous machines. PSO is a system that takes inspiration from the natural world and searches for the global maximum or minimum. By mimicking the behavior of swarming particles, PSO is a stochastic optimization method. In reaction to programmed commands, robots may do complicated activities while appearing human. Similar to a real-world swarm of robots, PSO's particle swarms represent a collective intelligence. That's why it shouldn’t be shocking that PSO has been recommended as a method of command for robotic swarms.

Keywords

RobotComputer scienceArtificial intelligenceHuman–computer interaction

Related papers

Browse all SWARM papers