52 citations · 81 across the 15 of their papers we have counts for
16 papers
Physics-informed reinforcement learning via probabilistic co-adjustment functions
Nat Wannawas, A. Aldo Faisal
Reinforcement learning of real-world tasks is very data inefficient, and extensive simulation-based modelling has become the dominant approach for training systems. However, in hum…
Enabling risk-aware Reinforcement Learning for medical interventions through uncertainty decomposition
Paul Festor, Giulia Luise, Matthieu Komorowski +1
Reinforcement Learning (RL) is emerging as tool for tackling complex control and decision-making problems. However, in high-risk environments such as healthcare, manufacturing, aut…
Neuromechanics-based Deep Reinforcement Learning of Neurostimulation Control in FES cycling
Nat Wannawas, Mahendran Subramanian, A. Aldo Faisal
Functional Electrical Stimulation (FES) can restore motion to a paralysed person's muscles. Yet, control stimulating many muscles to restore the practical function of entire limbs…
I am Robot: Neuromuscular Reinforcement Learning to Actuate Human Limbs through Functional Electrical Stimulation
Nat Wannawas, Ali Shafti, A. Aldo Faisal
Human movement disorders or paralysis lead to the loss of control of muscle activation and thus motor control. Functional Electrical Stimulation (FES) is an established and safe te…
Non-invasive Cognitive-level Human Interfacing for the Robotic Restoration of Reaching & Grasping
Ali Shafti, A. Aldo Faisal
Assistive and Wearable Robotics have the potential to support humans with different types of motor impairments to become independent and fulfil their activities of daily living suc…
Reinforcement Learning with Structured Hierarchical Grammar Representations of Actions
Petros Christodoulou, Robert Tjarko Lange, Ali Shafti +1
From a young age humans learn to use grammatical principles to hierarchically combine words into sentences. Action grammars is the parallel idea, that there is an underlying set of…
Human Visual Attention Prediction Boosts Learning & Performance of Autonomous Driving Agents
Alexander Makrigiorgos, Ali Shafti, Alex Harston +2
Autonomous driving is a multi-task problem requiring a deep understanding of the visual environment. End-to-end autonomous systems have attracted increasing interest as a method of…
Dot-to-Dot: Explainable Hierarchical Reinforcement Learning for Robotic Manipulation
Benjamin Beyret, Ali Shafti, A. Aldo Faisal
Robotic systems are ever more capable of automation and fulfilment of complex tasks, particularly with reliance on recent advances in intelligent systems, deep learning and artific…
Understanding the Artificial Intelligence Clinician and optimal treatment strategies for sepsis in intensive care
Matthieu Komorowski, Leo A. Celi, Omar Badawi +2
In this document, we explore in more detail our published work (Komorowski, Celi, Badawi, Gordon, & Faisal, 2018) for the benefit of the AI in Healthcare research community. In the…
Gaze-based, Context-aware Robotic System for Assisted Reaching and Grasping
Ali Shafti, Pavel Orlov, A. Aldo Faisal
Assistive robotic systems endeavour to support those with movement disabilities, enabling them to move again and regain functionality. Main issue with these systems is the complexi…
The Supernumerary Robotic 3rd Thumb for Skilled Music Tasks
James Cunningham, Anita Hapsari, Pierre Guilleminot +2
Wearable robotics bring the opportunity to augment human capability and performance, be it through prosthetics, exoskeletons, or supernumerary robotic limbs. The latter concept all…
Compact Convolutional Neural Networks for Multi-Class, Personalised, Closed-Loop EEG-BCI
Pablo Ortega, Cedric Colas, Aldo Faisal
For many people suffering from motor disabilities, assistive devices controlled with only brain activity are the only way to interact with their environment. Natural tasks often re…
Mechanomyography based closed-loop Functional Electrical Stimulation cycling system
Billy Woods, Mahendran Subramanian, Ali Shafti +1
Functional Electrical Stimulation (FES) systems are successful in restoring motor function and supporting paralyzed users. Commercially available FES products are open loop, meanin…
Towards an Embodied Semantic Fovea: Semantic 3D scene reconstruction from ego-centric eye-tracker videos
Mickey Li, Noyan Songur, Pavel Orlov +2
Incorporating the physical environment is essential for a complete understanding of human behavior in unconstrained every-day tasks. This is especially important in ego-centric tas…
FastOrient: Lightweight Computer Vision for Wrist Control in Assistive Robotic Grasping
Mireia Ruiz Maymo, Ali Shafti, A. Aldo Faisal
Wearable and Assistive robotics for human grasp support are broadly either tele-operated robotic arms or act through orthotic control of a paralyzed user's hand. Such devices requi…
Generalised Structural CNNs (SCNNs) for time series data with arbitrary graph topology
Thomas Teh, Chaiyawan Auepanwiriyakul, John Alexander Harston +1
Deep Learning methods, specifically convolutional neural networks (CNNs), have seen a lot of success in the domain of image-based data, where the data offers a clearly structured t…