Learn-Cars: Structured Deep Learning for Autonomous Driving (UoL, 2017-2018, Toyota Europe)

Learn-Cars: Structured Deep Learning for Autonomous Driving (UoL, 2017-2018, Toyota Europe)

We will follow a data-driven approach to achieve human-like driving styles with human-level adaptability and personalization to the human driver/passenger. We will estimate driving controllers…

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Robo-Pick: Robots for Autonomous Mushroom Picking (UoL, 2017 - 2018, Innovate UK)

Robo-Pick: Robots for Autonomous Mushroom Picking (UoL, 2017 – 2018, Innovate UK)

This project aims to develop a new robotic picking system to harvest fresh mushrooms reducing labour demands by ca. 66%. The work will be carried…

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Machine Learning Journal 2016: Probabilistic inference for determining options in reinforcement learning

Machine Learning Journal 2016: Probabilistic inference for determining options in reinforcement learning

Tasks that require many sequential decisions or complex solutions are hard to solve using conventional reinforcement learning algorithms. Based on the semi Markov decision process…

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JMLR 2016: Hierarchical Relative Entropy Policy Search

JMLR 2016: Hierarchical Relative Entropy Policy Search

Many reinforcement learning (RL) tasks, especially in robotics, consist of multiple sub-tasks thatĀ are strongly structured. Such task structures can be exploited by incorporating hierarchical policiesĀ that…

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Artificial Intelligence Journal: Model-based contextual policy search for data-efficient generalization of robot skills

Artificial Intelligence Journal: Model-based contextual policy search for data-efficient generalization of robot skills

In robotics, lower-level controllers are typically used to make the robot solve a specific task in a fixed context. For example, the lower-level controller can…

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LearnRobotS (TUDa, 2015-2018; DFG Project, SPP Autonomous Learning)

LearnRobotS (TUDa, 2015-2018; DFG Project, SPP Autonomous Learning)

The goal of this project is to develop a hierarchical learning system that decomposes complex motor skills into simpler elemental movements, also called movement primitives,…

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ROMANS (TUDa, 2015-2018; EU H2020 RIA)

ROMANS (TUDa, 2015-2018; EU H2020 RIA)

The RoMaNS (Robotic Manipulation for Nuclear Sort and Segregation) project will advance the state of the art in mixed autonomy for tele-manipulation, to solve a…

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NIPS 2013: Probabilistic Movement Primitives

NIPS 2013: Probabilistic Movement Primitives

Movement Primitives (MP) are a well-established approach for representing modular and re-usable robot movement generators. Many state-of-the-art robot learning successes are based MPs, due to…

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NIPS 2015: Model-Based Relative Entropy Stochastic Search

NIPS 2015: Model-Based Relative Entropy Stochastic Search

Stochastic search algorithms are general black-box optimizers. Due to their ease of use and their generality, they have recently also gained a lot of attention…

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