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06/27/2023
Trajectory Generation, Control, and Safety with Denoising Diffusion Probabilistic Models
We present a framework for safety-critical optimal control of physical s...
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12/29/2022
Discovering Efficient Periodic Behaviours in Mechanical Systems via Neural Approximators
It is well known that conservative mechanical systems exhibit local osci...
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08/27/2022
Deep Kernel Learning of Dynamical Models from High-Dimensional Noisy Data
This work proposes a Stochastic Variational Deep Kernel Learning method ...
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08/27/2022
Unsupervised Representation Learning in Deep Reinforcement Learning: A Review
This review addresses the problem of learning abstract representations o...
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07/08/2021
Towards Autonomous Pipeline Inspection with Hierarchical Reinforcement Learning
Inspection and maintenance are two crucial aspects of industrial pipelin...
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07/04/2021
Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics
Deep Reinforcement Learning has shown its ability in solving complicated...
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07/04/2021
Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces
Autonomous robots require high degrees of cognitive and motoric intellig...
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07/29/2020
Low Dimensional State Representation Learning with Reward-shaped Priors
Reinforcement Learning has been able to solve many complicated robotics ...
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02/10/2020
On Reward Shaping for Mobile Robot Navigation: A Reinforcement Learning and SLAM Based Approach
We present a map-less path planning algorithm based on Deep Reinforcemen...
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01/15/2020
The Penetration of Internet of Things in Robotics: Towards a Web of Robotic Things
As the Internet of Things (IoT) penetrates different domains and applica...
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10/29/2019