Papers
24
Total Citations
456
H-Index
10
About
Mihai Pomarlan is a robotics researcher whose work sits at the intersection of knowledge representation, cognitive reasoning, and autonomous robotic systems. His contributions are primarily focused on enabling robots to understand, plan, and execute complex tasks in dynamic real-world environments through sophisticated knowledge processing frameworks and ontological reasoning. Pomarlan's most influential contribution is his co-development of KnowRob 2.0, a second-generation knowledge processing framework for cognition-enabled robots, which has accumulated nearly 200 citations and represents a landmark advancement in robot cognition. Building on this foundation, his research spans natural language grounding for robotic instructions, assembly planning using OWL ontologies, and formal models of affordances — all aimed at giving robots richer, more flexible decision-making capabilities. His work on the SOMA framework further demonstrates his commitment to modeling everyday activities with both physical and social context. Beyond manipulation and planning, Pomarlan has contributed to mixed human-robot rescue teams, failure interpretation in automated execution, and multi-region inspection using motion planning. Collectively, his research addresses one of robotics' central challenges: equipping autonomous agents with the world knowledge and reasoning capacity needed to operate reliably alongside humans in unpredictable environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3OWL-enabled Assembly Planning for Robotic Agents27 citations · 2018
- 4A Formal Model of Affordances for Flexible Robotic Task Execution24 citations · 2020
- 5
- 6Cognition-enabled Framework for Mixed Human-Robot Rescue Teams18 citations · 2018
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- 9An Ontology for Failure Interpretation in Automated Planning and Execution13 citations · 2019
- 10