1 citations · 2 across the 7 of their papers we have counts for
8 papers
Robotic Untangling of Herbs and Salads with Parallel Grippers
Prabhakar Ray, Matthew Howard
The picking of one or more objects from an unsorted pile continues to be non-trivial for robotic systems. This is especially so when the pile consists of a granular material (GM) c…
Training Humans to Train Robots Dynamic Motor Skills
Marina Y. Aoyama, Matthew Howard
Learning from demonstration (LfD) is commonly considered to be a natural and intuitive way to allow novice users to teach motor skills to robots. However, it is important to acknow…
Exploiting Ergonomic Priors in Human-to-Robot Task Transfer
Jeevan Manavalan, Prabhakar Ray, Matthew Howard
In recent years, there has been a booming shift in the development of versatile, autonomous robots by introducing means to intuitively teach robots task-oriented behaviour by demon…
Improving Task-Parameterised Movement Learning Generalisation with Frame-Weighted Trajectory Generation
Aran Sena, Brendan Michael, Matthew Howard
Learning from Demonstration depends on a robot learner generalising its learned model to unseen conditions, as it is not feasible for a person to provide a demonstration set that a…
A Library for Constraint Consistent Learning
Yuchen Zhao, Jeevan Manavalan, Prabhakar Ray +2
This paper introduces the first, open source software library for Constraint Consistent Learning (CCL). It implements a family of data-driven methods that are capable of (i) learni…
Learning Singularity Avoidance
Jeevan Manavalan, Matthew Howard
With the increase in complexity of robotic systems and the rise in non-expert users, it can be assumed that task constraints are not explicitly known. In tasks where avoiding singu…