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Short info:

Currently I am a Lecturer at the University of Plymouth with the Centre for Robotics and Neural Systems. I keep strong links with Vislab-ISR - Instituto Superior Técnico where I worked as a researcher where I was involved in several research projects RobotCub, Handle, Contact and Mirror.

I am interested in the use of machine learning, control theory to create robots that are more robust and can interact and work with people. My research interests are on learning by imitation, artificial development and active learning approaches.

News:

Jointly with Pierre-Yves Oudeyer, I am organizing a special issue on: Active learning and intrinsically motivated exploration in robots for the IEEE Transactions on Autonomous Mental Development.
It has the support of IEEE CIS Technical committee on Autonomous Mental Development and the IEEE RAS Technical committee on Robot Learning.
myphoto
Manuel Lopes
Lecturer in Humanoid Robotics & Intelligent Systems
School of Computing and Mathematics
University of Plymouth
  22 Portland Square
Drake Circus,
Devon, PL4 8AA, UK
+44 1752 586305
manuel.lopes @ plymouth.ac.uk


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This images, inspired on Gibson's visual space, shows that the same gesture can have an huge difference in appearance. When doing imitation this visual perspective must be taken into account.

Image idea Manuel Lopes, Design Francisco Melo


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Baltazar grasps an object. Grasping is a very complex skill, it requires localizing the object, choose a good grasping point, plan a reaching behavior, execute the reaching and final close the hand.


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Baltazar likes to play with objects. In this case it is executing a task that was learned from a demonstration.


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Baltazar likes carrots!!!


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Robots are very complex machines. This is the team that design and built it.


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iCub can localize sounds. This is how it does it.


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Baltazar likes to imitate. Here it copies only the observed effects without taking into account the demonstrator.


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iCub likes to know everything that goes around him. An egosphere includes information about the motion, color, sound and edges that are around.


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When imitating we do not consider everything. When saying goodbye do you use the same elbow motion? Or just the hand motion?


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How can you learn a relation where a single input can have more than one output?


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Policy gradient methods are a good choice to improve control policies. How can you reuse all your data?


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Gesture imitation is easy. Or maybe not...


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One of the first pictures of the iCub head.


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One of the first pictures of the iCub head before being built!


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iCub is tested as a real child.


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iCub with very nice ears. Symmetrical ears are bad!


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Sometimes we need a good wizard of Oz.


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Imitation is not just for learning. It is also for social acceptance.


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A mosaic of the space around iCub.


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What is the stationary point of two learners that do not know that they are playing a game?


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A parallel mechanism was also studied as a potential iCub neck.


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Baltazar showing its skills.


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Baltazar design phase.