arXiv Open Access 2024

BANSAI: Towards Bridging the AI Adoption Gap in Industrial Robotics with Neurosymbolic Programming

Benjamin Alt Julia Dvorak Darko Katic Rainer Jäkel Michael Beetz +1 lainnya

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Abstrak

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 and optimization in modern industrial robot programming workflow. BANSAI conceptually unites several lines of prior research and proposes a path toward practical, real-world validation.

Topik & Kata Kunci

cs.RO cs.AI cs.CE cs.LG

Penulis (6)

Benjamin Alt

Julia Dvorak

Darko Katic

Rainer Jäkel

Michael Beetz

Gisela Lanza

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APA MLA BibTeX

Alt, B., Dvorak, J., Katic, D., Jäkel, R., Beetz, M., Lanza, G. (2024). BANSAI: Towards Bridging the AI Adoption Gap in Industrial Robotics with Neurosymbolic Programming. https://arxiv.org/abs/2404.13652

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓