1 code implementation • 20 Jul 2021 • Andrew Melnik, Augustin Harter, Christian Limberg, Krishan Rana, Niko Suenderhauf, Helge Ritter
This work discusses a learning approach to mask rewarding objects in images using sparse reward signals from an imitation learning dataset.
1 code implementation • 20 Feb 2019 • Sourav Garg, Madhu Babu V, Thanuja Dharmasiri, Stephen Hausler, Niko Suenderhauf, Swagat Kumar, Tom Drummond, Michael Milford
Visual place recognition (VPR) - the act of recognizing a familiar visual place - becomes difficult when there is extreme environmental appearance change or viewpoint change.
Robotics
no code implementations • 24 Apr 2018 • Mehdi Hosseinzadeh, Yasir Latif, Trung Pham, Niko Suenderhauf, Ian Reid
Simultaneous Localization And Mapping (SLAM) is a fundamental problem in mobile robotics.
1 code implementation • 16 Apr 2018 • Sourav Garg, Niko Suenderhauf, Michael Milford
Human visual scene understanding is so remarkable that we are able to recognize a revisited place when entering it from the opposite direction it was first visited, even in the presence of extreme variations in appearance.
1 code implementation • 28 Nov 2017 • Jake Bruce, Niko Suenderhauf, Piotr Mirowski, Raia Hadsell, Michael Milford
Recently, model-free reinforcement learning algorithms have been shown to solve challenging problems by learning from extensive interaction with the environment.
1 code implementation • 17 Sep 2016 • Jürgen Leitner, Adam W. Tow, Jake E. Dean, Niko Suenderhauf, Joseph W. Durham, Matthew Cooper, Markus Eich, Christopher Lehnert, Ruben Mangels, Christopher Mccool, Peter Kujala, Lachlan Nicholson, Trung Pham, James Sergeant, Liao Wu, Fangyi Zhang, Ben Upcroft, Peter Corke
We present a new physical benchmark challenge for robotic picking: the ACRV Picking Benchmark (APB).