51 citations · 54 across the 11 of their papers we have counts for
16 papers · 1 filter
Self-Supervised Localisation between Range Sensors and Overhead Imagery
Tim Y. Tang, Daniele De Martini, Shangzhe Wu +1
Publicly available satellite imagery can be an ubiquitous, cheap, and powerful tool for vehicle localisation when a prior sensor map is unavailable. However, satellite images are n…
Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision
David Williams, Daniele De Martini, Matthew Gadd +2
Reliable outdoor deployment of mobile robots requires the robust identification of permissible driving routes in a given environment. The performance of LiDAR and vision-based perc…
LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic
Tarlan Suleymanov, Matthew Gadd, Lars Kunze +1
This paper presents a system for improving the robustness of LiDAR lateral localisation systems. This is made possible by including detections of road boundaries which are invisibl…
Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance
Matthew Gadd, Daniele De Martini, Paul Newman
This paper details an application which yields significant improvements to the adeptness of place recognition with Frequency-Modulated Continuous-Wave radar - a commercially promis…
Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset
Will Maddern, Geoffrey Pascoe, Matthew Gadd +3
We describe the release of reference data towards a challenging long-term localisation and mapping benchmark based on the large-scale Oxford RobotCar Dataset. The release includes…
Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning
Ştefan Săftescu, Matthew Gadd, Daniele De Martini +2
This paper presents a system for robust, large-scale topological localisation using Frequency-Modulated Continuous-Wave (FMCW) scanning radar. We learn a metric space for embedding…