A Survey on UAV Computing Platforms: A Hardware Reliability Perspective

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 16; p. 6286
• Main Authors: Ahmed, Foisal, Jenihhin, Maksim
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 21.08.2022; MDPI
• Subjects: Algorithms; Artificial intelligence; Communication; computing platforms; cross-layer reliability; Drone aircraft; Drone vehicles; Drones; Failure; Failure modes; fault analysis; Fault tolerance; fault-resilience; Field programmable gate arrays; Global positioning systems; GPS; Neural networks; Reliability analysis; Review; Safety critical; Surveillance; Unmanned aerial vehicles; Wireless networks
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22166286

This study describes the Computing Platforms (CPs) and the hardware reliability issues of Unmanned Aerial Vehicles (UAVs), or drones, which recently attracted significant attention in mission and safety-critical applications demanding a failure-free operation. While the rapid development of the UAV technologies was recently reviewed by survey reports focusing on the architecture, cost, energy efficiency, communication, and civil application aspects, the computing platforms’ reliability perspective was overlooked. Moreover, due to the rising complexity and diversity of today’s UAV CPs, their reliability is becoming a prominent issue demanding up-to-date solutions tailored to the UAV specifics. The objective of this work is to address this gap, focusing on the hardware reliability aspect. This research studies the UAV CPs deployed for representative applications, specific fault and failure modes, and existing approaches for reliability assessment and enhancement in CPs for failure-free UAV operation. This study indicates how faults and failures occur in the various system layers of UAVs and analyzes open challenges. We advocate a concept of a cross-layer reliability model tailored to UAVs’ onboard intelligence and identify directions for future research in this area.