Angel Daruna
Papers
11
Total Citations
188
H-Index
7
About
Angel Daruna is a leading researcher in the intersection of robotics and artificial intelligence, specializing in semantic knowledge representation, reasoning, and robot common sense. Their work addresses a critical challenge: enabling autonomous robots to understand and manipulate objects in diverse, everyday environments by bridging the gap between raw perception and functional action. Daruna’s major contributions include the development of distributed neural representations for semantic knowledge, exemplified by the Robot Common Sense Embedding (RoboCSE) framework, which allows robots to generalize knowledge to novel situations while modeling uncertainty. They also introduced the Context-Aware Grasping Engine (CAGE), a seminal framework for semantic grasping that selects grasps based on both object properties and task constraints. With over 180 citations across their top publications, Daruna’s impact is evident in advancing explainable AI for robotics, as seen in their work on inference reconciliation for knowledge graph embeddings. Their research, including the Situated Bayesian Reasoning Framework and surveys on semantic reasoning, has laid foundational groundwork for scalable, context-aware robot intelligence, making them a key figure in the quest for truly autonomous service robots.
Research Focus
Key Achievements
Top Papers
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- 2CAGE: Context-Aware Grasping Engine44 citations · 2020
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- 4A survey of Semantic Reasoning frameworks for robotic systems19 citations · 2022
- 5RoboCSE: Robot Common Sense Embedding14 citations · 2019
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