1 citations · 1 across the 1 of their papers we have counts for
5 papers
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…
RSL-Net: Localising in Satellite Images From a Radar on the Ground
Tim Y. Tang, Daniele De Martini, Dan Barnes +1
This paper is about localising a vehicle in an overhead image using FMCW radar mounted on a ground vehicle. FMCW radar offers extraordinary promise and efficacy for vehicle localis…
Mapless Online Detection of Dynamic Objects in 3D Lidar
David J. Yoon, Tim Y. Tang, Timothy D. Barfoot
This paper presents a model-free, setting-independent method for online detection of dynamic objects in 3D lidar data. We explicitly compensate for the moving-while-scanning operat…
A White-Noise-On-Jerk Motion Prior for Continuous-Time Trajectory Estimation on SE(3)
Tim Y. Tang, David J. Yoon, Timothy D. Barfoot
Simultaneous trajectory estimation and mapping (STEAM) offers an efficient approach to continuous-time trajectory estimation, by representing the trajectory as a Gaussian process (…
Learning a Bias Correction for Lidar-only Motion Estimation
Tim Y. Tang, David J. Yoon, François Pomerleau +1
This paper presents a novel technique to correct for bias in a classical estimator using a learning approach. We apply a learned bias correction to a lidar-only motion estimation p…