Research on Embodied Intelligence Technology for Electric Power Equipment Based on Large‐Scale Pre‐Trained Models

Abstract

ABSTRACT With the development of electric power artificial intelligence (AI) technology, many complicated challenges emerged during application. Traditional AI algorithms work well in specialised tasks such as detection and classification. However, they are unlikely to solve general problems. Embodied intelligence is a promising technology with the potential to address problems in both general and specialised areas. Instead of learning from primary datasets such as photos and texts, embodied intelligence learns through interactions with the surrounding environments from an egocentric perception similar to that of human beings. This provides embodied intelligence algorithms with adaptability and flexibility. This paper aims to provide an extensive research for the field of embodied intelligence in two aspects: navigating and operating. The navigation simulation result shows a notable recall enhancement of over 9.74% compared to other algorithms. The operating simulation achieves an average success rate of 50%, which is the first in this area. Eventually, with the new insights revealed through the simulation, this paper will provide more suggestions for the future development of embodied intelligence in electric power artificial intelligence.