59 citations · 457 across the 92 of their papers we have counts for
11 papers · 2 filters
Surfing on an uncertain edge: Precision cutting of soft tissue using torque-based medium classification
Artūras Straižys, Michael Burke, Subramanian Ramamoorthy
Precision cutting of soft-tissue remains a challenging problem in robotics, due to the complex and unpredictable mechanical behaviour of tissue under manipulation. Here, we conside…
Disentangled Relational Representations for Explaining and Learning from Demonstration
Yordan Hristov, Daniel Angelov, Michael Burke +2
Learning from demonstration is an effective method for human users to instruct desired robot behaviour. However, for most non-trivial tasks of practical interest, efficient learnin…
Composing Diverse Policies for Temporally Extended Tasks
Daniel Angelov, Yordan Hristov, Michael Burke +1
Robot control policies for temporally extended and sequenced tasks are often characterized by discontinuous switches between different local dynamics. These change-points are often…
Vid2Param: Modelling of Dynamics Parameters from Video
Martin Asenov, Michael Burke, Daniel Angelov +3
Videos provide a rich source of information, but it is generally hard to extract dynamical parameters of interest. Inferring those parameters from a video stream would be beneficia…
Hybrid system identification using switching density networks
Michael Burke, Yordan Hristov, Subramanian Ramamoorthy
Behaviour cloning is a commonly used strategy for imitation learning and can be extremely effective in constrained domains. However, in cases where the dynamics of an environment m…
DynoPlan: Combining Motion Planning and Deep Neural Network based Controllers for Safe HRL
Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy
Many realistic robotics tasks are best solved compositionally, through control architectures that sequentially invoke primitives and achieve error correction through the use of loo…
Learning Grasp Affordance Reasoning through Semantic Relations
Paola Ardón, Èric Pairet, Ronald P. A. Petrick +2
Reasoning about object affordances allows an autonomous agent to perform generalised manipulation tasks among object instances. While current approaches to grasp affordance estimat…
Reasoning on Grasp-Action Affordances
Paola Ardón, Èric Pairet, Ron Petrick +2
Artificial intelligence is essential to succeed in challenging activities that involve dynamic environments, such as object manipulation tasks in indoor scenes. Most of the state-o…
To Stir or Not to Stir: Online Estimation of Liquid Properties for Pouring Actions
Tatiana Lopez-Guevara, Rita Pucci, Nicholas Taylor +3
Our brains are able to exploit coarse physical models of fluids to solve everyday manipulation tasks. There has been considerable interest in developing such a capability in robots…
From explanation to synthesis: Compositional program induction for learning from demonstration
Michael Burke, Svetlin Penkov, Subramanian Ramamoorthy
Hybrid systems are a compact and natural mechanism with which to address problems in robotics. This work introduces an approach to learning hybrid systems from demonstrations, with…
Active Localization of Gas Leaks using Fluid Simulation
Martin Asenov, Marius Rutkauskas, Derryck Reid +2
Sensors are routinely mounted on robots to acquire various forms of measurements in spatio-temporal fields. Locating features within these fields and reconstruction (mapping) of th…