See and Avoid Using Onboard Computer Vision

John Lai, Jason J. Ford, Luis Mejias, Peter O’Shea and Rod Walker

Australian Research Centre for Aerospace Automation, Queensland University of Technology Australia

10.1 Introduction

10.1.1 Background

The integration of unmanned aircraft into civil airspace is a complex issue. One key question is whether unmanned aircraft can operate just as safely as their manned counterparts. The absence of a human pilot in unmanned aircraft automatically points to a deficiency – that is, the lack of an inherent see-and-avoid capability. To date, regulators have mandated that an ‘equivalent level of safety’ be demonstrated before UAVs are permitted to routinely operate in civil airspace. This chapter proposes techniques, methods, and hardware integrations that describe a ‘sense-and-avoid’ system designed to address the lack of a see-and-avoid capability in unmanned aerial vehicles (UAVs).

10.1.2 Outline of the SAA Problem

Non-cooperative collision avoidance (or sense-and-avoid) for UAVs has been identified as one of the most significant challenges facing the integration of unmanned aircraft into the national airspace [1, 2]. Here, the term ‘sense’ relates to the use of sensor information to automatically detect possible aircraft conflicts, whilst the term ‘avoid’ relates to the automated control actions used to avoid any detected collisions. Much of the previous research effort on the sense-and-avoid problem has been focused on the ‘sense’ or conflict ...

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