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BANSAI: Towards Bridging the AI Adoption Gap in Industrial Robotics with Neurosymbolic Programming
April 23, 2024, 4:43 a.m. | Benjamin Alt, Julia Dvorak, Darko Katic, Rainer J\"akel, Michael Beetz, Gisela Lanza
cs.LG updates on arXiv.org arxiv.org
Abstract: Over the past decade, deep learning helped solve manipulation problems across all domains of robotics. At the same time, industrial robots continue to be programmed overwhelmingly using traditional program representations and interfaces. This paper undertakes an analysis of this "AI adoption gap" from an industry practitioner's perspective. In response, we propose the BANSAI approach (Bridging the AI Adoption Gap via Neurosymbolic AI). It systematically leverages principles of neurosymbolic AI to establish data-driven, subsymbolic program synthesis …
abstract adoption ai adoption analysis arxiv cs.ai cs.ce cs.lg cs.ro deep learning domains gap industrial industrial robotics industrial robots interfaces manipulation paper programming robotics robots solve type
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