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Robot Learning Seminar Series

The Robot Learning Seminar Series is an initiative which began in December 2022, where we are organising regular, in-person seminars, hosted at Imperial College London. These seminars will be broadly on the topic of robot learning, but will also overlap with complementary areas in robotics, machine learning, and computer vision. See below for details of past and upcoming seminars, and I hope to see many of you there from Imperial College and beyond! For enquiries, please contact Edward Johns at e.johns@imperial.ac.uk.

Upcoming Seminars

Jens Kober

(TU Delft)

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When? Wednesday 20th November, 2pm - 3pm

 

Where? Huxley 139 (Directions: click here)

 

Talk Title: Robots Learning Through Interactions

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Abstract: The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Complexity arises from interactions with their environment and humans, dealing with high-dimensional input data, non-linear dynamics in general and contacts in particular, multiple reference frames, and variability in objects, environments, tasks, and human behavior. A human teacher is always involved in the learning process, either directly (providing data) or indirectly (designing the optimization criterion), which raises the question: How to best make use of the interactions with the human teacher to render the learning process efficient and effective? In this talk I’ll argue that there are tremendous benefits in having a human teacher intermittently interact with a robot also while it is learning. I will discuss various methods we have developed in the fields of supervised learning, imitation learning, reinforcement learning, and interactive learning. All these concepts will be illustrated with benchmark tasks and real robot experiments ranging from fun (ball-in-a-cup) to more applied (retail environments).

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Bio: Jens Kober is an associate professor at the TU Delft, Netherlands. He worked as a postdoctoral scholar jointly at the CoR-Lab, Bielefeld University, Germany and at the Honda Research Institute Europe, Germany. He graduated in 2012 with a PhD Degree in Engineering from TU Darmstadt and the MPI for Intelligent Systems. For his research he received the annually awarded Georges Giralt PhD Award for the best PhD thesis in robotics in Europe, the 2018 IEEE RAS Early Academic Career Award, the 2022 RSS Early Career Award, and has received an ERC Starting grant. His research interests include motor skill learning, (deep) reinforcement learning, imitation learning, interactive learning, and machine learning for control.

Webpagehttp://www.jenskober.de/

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Past Seminars

Speaker

Title

Date

Video

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Markus Wulfmeier
Google DeepMind

Reinforcement Learning

in the Age of Large Data

20th June
2024

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Nathan Lepora
University of Bristol

Tactile Robot Dexterity

24th April
2024

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Amanda Prorok
University of Cambridge

Graph Neural Network Based Interaction Models

for Collaborative Control

in Multi-Robot Systems

24th January 2024

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Frontiers in Embodied AI

for Autonomous Driving

15th November
2023

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Martin Riedmiller
Google DeepMind

Data-efficient RL Agents -

how to build and why they matter

12th July
2023

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Dimitrios Kanoulas
University College London (UCL)

Cognitive Real-World

Loco-Manipulation

3rd May
2023

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Ingmar Posner
University of Oxford

Learning to Perceive and to Act - Disentangling Tales from (Structured) Latent Space

25th January 2023

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Subramanian Ramamoorthy
University of Edinburgh

Towards a holistic view of learning from demonstration: Case studies involving dexterous manipulation

2nd December
2022

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