A survey on unmanned aerial vehicle collision avoidance systems

Abstract

Collision avoidance is a key factor in enabling the integration of unmanned aerial vehicle into real life use, whether it is in military or civil application. For a long time there have been a large number of works to address this problem; therefore a comparative summary of them would be desirable. This paper presents a survey on the major collision avoidance systems developed in up to date publications. Each collision avoidance system contains two main parts: sensing and detection, and collision avoidance. Based on their characteristics each part is divided into different categories; and those categories are explained, compared and discussed about advantages and disadvantages in this paper.

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• Deep Learning based Multi-Modal Sensing for Tracking and State Extraction of Small Quadcopters
• Designing the Waveform Bandwidth and Time Duration of Automotive Radars for Better Collision Warning Performance