Papers
19
Total Citations
250
H-Index
9
About
John Bateman is a leading figure in cognitive robotics and spatial AI, whose work bridges formal ontology, human-robot interaction, and situated reasoning. His research centers on how robots can represent, communicate, and act upon spatial and social knowledge—enabling more flexible, dialogue-driven autonomy. Bateman’s most influential contribution is the development of formal spatial ontologies for robot navigation and shared control, exemplified by his highly cited 2007 paper on spatial knowledge representation for human-robot interaction (39 citations) and his 2005 work on modelling robot navigation using formal spatial ontology (35 citations). He has also advanced the field of affordance-based reasoning, notably in his 2020 formal model of affordances for flexible task execution (24 citations), and co-developed the SkillMaN framework for perception-driven robotic manipulation (23 citations). Bateman’s impact extends to failure interpretation in automated planning and the foundational Socio-Physical Model of Activities (SOMA), which integrates physical and social context for autonomous agents. With over 200 total citations across his most-cited works, his research is essential reading for anyone interested in how robots can understand and act intelligently in human environments.
Research Focus
Key Achievements
Top Papers
- 1Spatial Knowledge Representation for Human-Robot Interaction39 citations · 2007
- 2Modelling Models of Robot Navigation Using Formal Spatial Ontology35 citations · 2005
- 3Towards Dialogue Based Shared Control of Navigating Robots28 citations · 2005
- 4A Formal Model of Affordances for Flexible Robotic Task Execution24 citations · 2020
- 5
- 6Dialog-Based 3D-Image Recognition Using a Domain Ontology20 citations · 2007
- 7
- 8An Ontology for Failure Interpretation in Automated Planning and Execution13 citations · 2019
- 9
- 10Embodied contextualization: Towards a multistratal ontological treatment7 citations · 2019