Peter Robinson

Papers

Total Citations

H-Index

About

Peter Robinson is a researcher specializing in robotic agent programming, multi-agent systems, and cognitive robotics. His work sits at the intersection of artificial intelligence and autonomous systems, with a particular focus on developing principled frameworks for programming intelligent robotic agents. Robinson's most significant contribution is TeleoR, an extension of Nilsson's Teleo-Reactive programming language, which provides a robust rule-based paradigm for robotic agent programming. First introduced in 2015 and garnering 15 citations, TeleoR enables robots to respond dynamically to rapidly changing environments through guard-action rule sequences. He subsequently extended this work to support concurrent task programming, demonstrating a sustained commitment to making robotic systems more capable and flexible. Beyond individual robot programming, Robinson has contributed to multi-agent coordination, exploring genetic-based machine learning for dynamic priority assignment in path planning conflicts — work that has attracted 10 citations. His 2016 framework for integrating symbolic and sub-symbolic representations further reflects his ambition to advance cognitive robotics architectures that bridge traditional AI reasoning with neural and perceptual processing. Robinson's body of work, though focused on a specialised niche, reflects a coherent research vision: building expressive, principled, and practically deployable programming tools for autonomous robotic systems.