• Publications
  • Influence
SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights
TLDR
A new approach to visual navigation under changing conditions dubbed SeqSLAM, which removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. Expand
On the performance of ConvNet features for place recognition
TLDR
It is confirmed that networks trained for semantic place categorization also perform better at (specific) place recognition when faced with severe appearance changes and provide a reference for which networks and layers are optimal for different aspects of the place recognition problem. Expand
Place Recognition with ConvNet Landmarks: Viewpoint-Robust, Condition-Robust, Training-Free
TLDR
An approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition using the astonishing power of convolutional neural network features to identify matching landmark proposals between images. Expand
Visual Place Recognition: A Survey
TLDR
A survey of the visual place recognition research landscape is presented, introducing the concepts behind place recognition, how a “place” is defined in a robotics context, and the major components of a place recognition system. Expand
Mapping a Suburb With a Single Camera Using a Biologically Inspired SLAM System
TLDR
A biologically inspired approach to vision-only simultaneous localization and mapping (SLAM) on ground-based platforms based on computational models of the rodent hippocampus is described, coupled with a lightweight vision system that provides odometry and appearance information. Expand
RatSLAM: a hippocampal model for simultaneous localization and mapping
TLDR
RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot, and uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Expand
Deep learning features at scale for visual place recognition
TLDR
This paper trains, at large scale, two CNN architectures for the specific place recognition task and employs a multi-scale feature encoding method to generate condition- and viewpoint-invariant features. Expand
Persistent Navigation and Mapping using a Biologically Inspired SLAM System
TLDR
This work investigated the persistent navigation and mapping problem in the context of an autonomous robot that performs mock deliveries in a working office environment over a two-week period and found the solution was based on the biologically inspired visual SLAM system, RatSLAM. Expand
OpenFABMAP: An open source toolbox for appearance-based loop closure detection
TLDR
OpenFABMAP is described, a fully open source implementation of the original FAB-MAP algorithm that provides a number of configurable options including rapid codebook training and interest point feature tuning and the advantages of quick algorithm customisation. Expand
FAB-MAP + RatSLAM: Appearance-based SLAM for multiple times of day
TLDR
This work fuses the probabilistic local feature based data association method of FAB-MAP with the pose cell filtering and experience mapping of RatSLAM to form a single amalgamation of methods forAppearance-based mapping and localisation. Expand
...
1
2
3
4
5
...