Papers
11
Total Citations
68
H-Index
4
About
Esther Aguado is a leading researcher in autonomous robotics, with a focus on enhancing robot dependability through knowledge representation and metacontrol. Her work primarily addresses the challenges of long-term autonomy in complex environments, particularly for underwater and mining robots. Aguado’s major contributions include developing functional self-awareness and metacontrol frameworks, as demonstrated in her highly cited 2021 paper (26 citations), which enables robots like the UX-1 mine explorer to adapt to internal and external disturbances. She has also advanced reconfigurable skills in ROS, creating modeling tools that simplify the implementation of adaptable architectures (10 citations). Her involvement in the EU-funded ROBOMINERS project has led to the development of highly configurable mining robot prototypes (7 citations), while her surveys on ontology-enabled processes (6 citations) provide foundational insights for trustworthy autonomous systems. Aguado’s interdisciplinary approach extends to exploring machine consciousness and human-robot interaction, with notable work on wildness in robots to improve user engagement. Her research, supported by formal models in Maude and category theory, underscores her impact on engineering robust, self-aware robots for real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy26 citations · 2021
- 2A Modeling Tool for Reconfigurable Skills in ROS10 citations · 2021
- 3
- 4A survey of ontology-enabled processes for dependable robot autonomy6 citations · 2024
- 5
- 6Using Ontologies in Autonomous Robots Engineering4 citations · 2021
- 7A Formal Model of Metacontrol in Maude3 citations · 2022
- 8Understanding and Machine Consciousness3 citations · 2020
- 9Codifying Wildness: Wild Behaviour for Improving Human-Robot Interaction2 citations · 2023
- 10Category Theory for Autonomous Robots: The Marathon 2 Use Case2 citations · 2024