Localisation

//Localisation

From Dusk till Dawn: Localisation at Night using Artificial Light Sources

Abstract—This paper is about localising at night in urban environments using vision. Despite it being dark exactly half of the time, surprisingly little attention has been given to this problem. A defining aspect of night-time urban scenes is the presence and effect of artificial lighting -- be that in the form of street or interior lighting through windows. By [...]

From Dusk till Dawn: Localisation at Night using Artificial Light Sources 2016-10-22T19:49:34+00:00

Work Smart, Not Hard: Recalling Relevant Experiences for Vast-Scale but Time-Constrained Localisation

This paper is about life-long vast-scale localisation in spite of changes in weather, lighting and scene structure. Building upon our previous work in Experience-based Navigation, we continually grow and curate a visual map of the world that explicitly supports multiple representations of the same place. We refer to these representations as experiences, where a single [...]

Work Smart, Not Hard: Recalling Relevant Experiences for Vast-Scale but Time-Constrained Localisation 2016-10-22T19:49:34+00:00

Leveraging Experience for Long-Term LIDAR Localisation In Changing Cities

 Successful approaches to autonomous vehicle localisation and navigation typically involve 3D LIDAR scanners and a static, curated 3D map, both of which are expensive to acquire and maintain. We propose an experience-based approach to matching a local 3D swathe built using a push-broom 2D LIDAR to a number of prior 3D maps, each of which [...]

Leveraging Experience for Long-Term LIDAR Localisation In Changing Cities 2017-03-21T11:44:36+00:00

FARLAP: Fast Robust Localisation using Appearance Priors

https://www.youtube.com/watch?v=8T6_510P-LM This paper is concerned with large-scale localisation at city scales with monocular cameras. Our primary motivation lies with the development of autonomous road vehicles — an application domain in which low-cost sensing is particularly important. Here we present a method for localising against a textured 3-dimensional prior mesh using a monocular camera. [...]

FARLAP: Fast Robust Localisation using Appearance Priors 2017-03-21T12:20:39+00:00

Real-Time Bounded-Error Pose Estimation for Road Vehicles Using Vision

This paper is about online, constant-time pose es- timation for road vehicles. We exploit both the state of the art in vision based SLAM and the wide availability of overhead imagery of road networks. We show that by formulating the pose estimation problem in a relative sense, we can estimate the vehicle pose in real-time [...]

Real-Time Bounded-Error Pose Estimation for Road Vehicles Using Vision 2016-10-22T19:49:34+00:00

Vast Scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment

This shows the 121-km path taken between Oxford in the upper left and London in the bottom right. We compute visual estimates for 89.4% of this trajectory and fall back on inertial sensing for the remainder. Abstract - In this paper we describe a relative approach to simultaneous localisation and mapping, based on the [...]

Vast Scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment 2016-10-22T19:49:34+00:00

Road vehicle localization with 2D push-broom lidar and 3D priors

In this paper we describe and demonstrate a method for precisely localizing a road vehicle using a single push-broom 2D laser scanner while leveraging a prior 3D survey. In contrast to conventional scan matching, our laser is oriented downwards, thus causing continual ground strike. Our method exploits this to produce a small 3D swathe of laser data which can be matched [...]

Road vehicle localization with 2D push-broom lidar and 3D priors 2016-10-22T19:49:35+00:00

Laser-only road-vehicle localization with dual 2D push-broom LIDARS and 3D priors

In this paper we consider long-term navigation using fixed 2D LIDARs. We consider how localization algorithms based on scan-matching - commonly used in indoor environments - are prone to failure when exposed to a challenging real-world outdoor environment. The driving motivation behind this work is to produce a simple, robust system that can be utilized repeatedly over a long period, rather than [...]

Laser-only road-vehicle localization with dual 2D push-broom LIDARS and 3D priors 2016-10-22T19:49:35+00:00

LAPS – Localisation using Appearance of Prior Structure: 6-DOF Monocular Camera Localisation using Prior Pointclouds

Abstract— This paper is about pose estimation using monocular cameras with a 3D laser pointcloud as a workspace prior. We have in mind autonomous transport systems in which low cost vehicles equipped with monocular cameras are furnished with preprocessed 3D lidar workspaces surveys. Our inherently cross-modal approach offers robustness to changes in scene lighting and [...]

LAPS – Localisation using Appearance of Prior Structure: 6-DOF Monocular Camera Localisation using Prior Pointclouds 2016-10-22T19:49:35+00:00

FAB-MAP 3D: Topological Mapping with Spatial and Visual Appearance

Abstract— This paper describes a probabilistic framework for appearance based navigation and mapping using spatial and visual appearance data. Like much recent work on appearance based navigation we adopt a bag-of-words approach in which positive or negative observations of visual words in a scene are used to discriminate between already visited and new places. In [...]

FAB-MAP 3D: Topological Mapping with Spatial and Visual Appearance 2016-10-22T19:49:35+00:00