Research within SLMC
The SLMC group has a broad and highly inter-disciplinary research agenda spanning statistical machine learning, formal learning theory, learning in connectionist systems (artificial and biological); robotic, humanoid and biological motor control, adaptive/learning control; and multimodal cue integration and attentional strategies.
- Some of the currently active and archived project pages are listed here.
- A more detailed (somewhat dated) description of some of the projects can be found here.
SoftwareSome of our work has resulted in software packages that may be useful to other researchers or practitioners:
LWPRLocally Weighted Projection Regression (LWPR) is an algorithm developed in our group that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. We developed a C-library with wrappers for C++, Matlab/Octave, and Python.
EXOTicaThe EXOTica library is a generic Optimisation Toolset for Robotics platforms, written in C++. Its motivation is to provide a more streamlined process for developing algorithms for such tasks as Inverse-Kinematics and Trajectory Optimisation.
PublicationsAn up-to-date publication list can be found here.
Some of the topics of recent interest are listed below (with links to
- Statistical Learning
- Visual Attention & Oculomotor Control (papers)
- Real Time Learning for Robot Control & High Dimensional Systems (papers)
- Dimensionality Reduction (papers)
- Multimodal Learning and Cue Integration
- Haptic Discrimination: Encoding and Decoding Strategies