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个人简介
My research interests are in the areas of computer and robot vision, to address two questions: (i) how to develop artificial (robotic) systems that use vision and other sensing modalities to "understand" the world around them and (ii) to investigate, model and understand how vision is used in biological systems like insects or humans.
One example is vision based-navigation, motion perception and control, including how to use video imagery in closed loop for mapping and control of land, air and underwater vehicles. It often requires the design of task-specific camera geometries, like omnidirectional and space variant cameras. This research draws inspiration from biology where evolution has lead to specialized and sophisticated solutions (both eye design and processing) adapted to the behaviour of the various species (e.g. compound eyes, foveal cameras).
Another main area of research is cognitive humanoid systems. Together with neuroscientists and developmental psychologists, we aim to understand human cognition, sensorimotor coordination and learning, as well as to design robotic systems with learning and adaptation capabilities. Flagship projects have addressed the models of mirror neurons to enhance the ability of human action recognition, imitation and programming by demonstration. We have proposed a model of object affordances that improves a robot’s ability to manipulate objects, ground language and choose tools that are adequate to a given function.
One example is vision based-navigation, motion perception and control, including how to use video imagery in closed loop for mapping and control of land, air and underwater vehicles. It often requires the design of task-specific camera geometries, like omnidirectional and space variant cameras. This research draws inspiration from biology where evolution has lead to specialized and sophisticated solutions (both eye design and processing) adapted to the behaviour of the various species (e.g. compound eyes, foveal cameras).
Another main area of research is cognitive humanoid systems. Together with neuroscientists and developmental psychologists, we aim to understand human cognition, sensorimotor coordination and learning, as well as to design robotic systems with learning and adaptation capabilities. Flagship projects have addressed the models of mirror neurons to enhance the ability of human action recognition, imitation and programming by demonstration. We have proposed a model of object affordances that improves a robot’s ability to manipulate objects, ground language and choose tools that are adequate to a given function.
研究兴趣
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Cognitive Processingno. 1 (2024): 173-187
Ines Rito Lima,José Santos-Victor
2023 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)pp.37-43, (2023)
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2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA (2023): 3815-3822
2023 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)pp.2-2, (2023)
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AUTONOMOUS ROBOTSno. 4 (2023): 453-464
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMSno. 4 (2023): 1948-1958
IEEE Transactions on Cognitive and Developmental Systemsno. 3 (2023): 985-999
FRONTIERS IN NEUROERGONOMICS (2023): 1080794-1080794
2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (2023): 9824-9831
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