Geo-Referenced Mapping through an Anti-Collision Radar Aboard an Unmanned Aerial System

Lapo Miccinesi,Massimiliano Pieraccini,Michele Basso,Tommaso Consumi,Alessandra Beni,Luca Bigazzi,Enrico Boni

doi:10.3390/drones6030072

Abstract

Unmanned aerial systems (UASs) have enormous potential in many fields of application, especially when used in combination with autonomous guidance. An open challenge for safe autonomous flight is to rely on a mapping system for local positioning and obstacle avoidance. In this article, the authors propose a radar-based mapping system both for obstacle detection and for path planning. The radar equipment used is a single-chip device originally developed for automotive applications that has good resolution in azimuth, but poor resolution in elevation. This limitation can be critical for UAS application, and it must be considered for obstacle-avoidance maneuvers and for autonomous path-planning selection. However, the radar-mapping system proposed in this paper was successfully tested in the following different scenarios: a single metallic target in grass, a vegetated scenario, and in the close proximity of a ruined building.

Highlights

Recent technological advances made in unmanned aerial systems (UASs), especially in combination with autonomous flights, could have a major impact on civilian tasks [1]
They could enable the provision of social services, such as the delivery of goods, drugs and sanitary equipment, but could perform environmental monitoring in remote regions [2]. Since these applications would involve flights performed in complex outdoor scenarios, capabilities for autonomous obstacle detection and avoidance are of paramount importance
The aim of this article is to present some preliminary tests of a radar aboard a UAS that is able to both operate as obstacle-avoidance equipment, and is able to provide reliable mapping of its surrounding area that could be used to elaborate effective de

Summary

Introduction

Recent technological advances made in unmanned aerial systems (UASs), especially in combination with autonomous flights, could have a major impact on civilian tasks [1]. They could enable the provision of social services, such as the delivery of goods, drugs and sanitary equipment, but could perform environmental monitoring in remote regions [2]. Since these applications would involve flights performed in complex outdoor scenarios, capabilities for autonomous obstacle detection and avoidance are of paramount importance. A mapping procedure of the surrounding area would enable the detection and avoidance of obstacles, and the elaboration of effective decommitment strategies

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