Developmental Cognitive Robotics
Learn to design robots with human-like learning abilities using principles from child psychology and cognitive development theories.
Learn to design robots with human-like learning abilities using principles from child psychology and cognitive development theories.
This comprehensive course explores developmental cognitive robotics, bridging robotics engineering with child psychology. Students learn how to develop robots with advanced sensorimotor and cognitive abilities inspired by human development. The curriculum covers essential topics including intrinsic motivation, motor learning, social interaction, and language acquisition in robots. Through detailed exploration of psychological theories and robotics technology, participants gain practical knowledge in designing robots that can learn and adapt like humans. Created in collaboration with Professor Matthew Schlesinger, this course offers valuable insights for both technical and cognitive science professionals.
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What you'll learn
Design robots with advanced cognitive and sensorimotor capabilities
Apply developmental psychology principles to robotics
Implement intrinsic motivation in robotic systems
Develop motor and perceptual learning mechanisms
Create systems for robot social interaction and language learning
Understand computational models of cognition and behavior
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This innovative course combines developmental psychology with robotics engineering to teach the principles of creating cognitively advanced robots. The curriculum explores how child psychology theories can be applied to develop sophisticated robotic systems with human-like learning capabilities. Students learn about intrinsic motivation, motor and perceptual learning, social interaction, and language acquisition in the context of robotics. The course covers both theoretical foundations from developmental psychology and neuroscience, as well as practical applications in robotics technology, including exposure to major robot platforms and simulators.
Fee Structure
Instructors
1 Course
Distinguished Robotics Expert and Cognitive Systems Pioneer
Angelo Cangelosi serves as Professor of Machine Learning and Robotics at the University of Manchester and Turing Fellow at the Alan Turing Institute. After completing studies in psychology and cognitive science at the Universities of Rome La Sapienza and Genoa, he has established himself as a leading researcher in developmental robotics and human-robot interaction. His work focuses on language grounding and embodiment in humanoid robots, with applications of neuromorphic systems for robot learning. As coordinator of major European projects including APRIL, THRIVE++, and MoveCare, he has secured over £30m in research grants. His academic contributions include more than 250 scientific publications and two influential books on developmental robotics. As former Chair of the IEEE Technical Committee on Autonomous Mental Development and Editor of multiple prestigious journals, he continues to shape the field of cognitive robotics while fostering international collaboration through visiting professorships at Waseda University and various Italian institutions.
1 Course
Distinguished Developmental Robotics Expert and Cognitive Scientist
Matthew Schlesinger serves as Professor of Brain and Cognitive Sciences in the Department of Psychology and Adjunct Associate Professor of Electrical and Computer Engineering at Southern Illinois University Carbondale. His research focuses on understanding cognitive development through computational modeling and robotic simulations. As director of the SIU Vision Lab, he leads research exploring how vision functions as an improvable skill and guides motor skill development. His groundbreaking work includes co-authoring "Developmental Robotics: From Babies to Robots" with Angelo Cangelosi, published by MIT Press, which explores how understanding infant learning can inform robot development
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Frequently asked questions
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