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About

Nicholas Cote is a leading researcher at the intersection of robotic construction, artificial intelligence, and architectural fabrication. His work focuses on enabling robots to perform complex assembly tasks with the precision and adaptability required for real-world construction, particularly in timber and unitized enclosure systems. Cote’s major contributions include pioneering the use of reinforcement learning for robotic assembly of timber joints with form-closure, a breakthrough that addresses the challenges of tolerances and small-series production—his 2021 paper on this topic has garnered 127 citations, underscoring its impact. He has also advanced vision-guided, closed-loop robotic assembly, making these technologies more accessible for prefabrication and in situ robotics. Most recently, Cote has explored the use of Large Language Models, such as ChatGPT, to automate programming for adaptive robotic assembly, reducing the labor-intensive, domain-specific coding traditionally required. His work, spanning from highly cited foundational studies to cutting-edge AI integration, positions him as a key innovator in making robotic construction more intelligent, flexible, and practical for the built environment.