This paper is about long-term navigation in environments whose appearance changes over
time, suddenly or gradually. We describe, implement and validate an approach which allows …

In this paper we propose the use of an illumination invariant transform to improve many
aspects of visual localisation, mapping and scene classification for autonomous road …

This paper is about localising across extreme lighting and weather conditions. We depart
from the traditional point-feature-based approach as matching under dramatic appearance …

This paper is about extending the reach and endurance of outdoor localisation using stereo
vision. At the heart of the localisation is the fundamental task of discovering feature …

Vision-based, route-following algorithms enable autonomous robots to repeat manually
taught paths over long distances using inexpensive vision sensors. However, these methods …

Robots and autonomous systems need to know where they are within a map to navigate
effectively. Thus, simultaneous localization and mapping or SLAM is a common building …

Fully autonomous mobile robots have a multitude of potential applications, but guaranteeing
robust navigation performance remains an open research problem. For many tasks such as …

In this paper, we present a lifelong-learning multisensor system for pedestrian detection in
adverse weather conditions. The proposed method combines two people detection …

We present an experimental investigation of a multi-sensor fusion-learning system for
detecting pedestrians in foggy weather conditions. The method combines two pipelines for …

Nowadays, most agricultural robots rely on precise and expensive localisation, typically
based on global navigation satellite systems (GNSS) and real-time kinematic (RTK) …