5 accepted papers
This paper presents a novel collision avoidance method for Autonomous Surface Vessels (ASVs) that considers nuanced risk and COLREG profiles to determine an optimal safe manoeuvre. The COLREGs are a set of collision regulations defined by the International Maritime Organisation by which all complian
Visual Place Recognition (VPR) systems often have imperfect performance, affecting the ‘integrity’ of position estimates and subsequent robot navigation decisions. Previously, SVM classifiers have been used to monitor VPR integrity. This research introduces a novel Multi-Layer Perceptron (MLP) integ
While substantial progress has been made in the absolute performance of localization and Visual Place Recognition (VPR) techniques, it is becoming increasingly clear from translating these systems into applications that other capabilities like integrity and predictability are just as important, espe…
Visual Place Recognition (VPR) is a key component of many robot localization and mapping system processing pipelines, providing loop closure and coarse topological localization priors for pose refinement stages. When deploying these systems in the real-world, system self-characterization of when it
The commercial use of unmanned aerial vehicles (UAVs) would be enhanced by an ability to sense and avoid potential mid-air collision threats. In this letter, we propose a new approach to aircraft detection for long-range vision-based sense and avoid. We first train a deep convolutional neural networ