Abstract

Considering that the actual operating environment of UAV is complex and easily disturbed by the space environment of urban buildings, the RoutE Planning Algorithm of Resilience Enhancement (REPARE) for UAV 3D route planning based on the A* algorithm and artificial potential fields algorithm is carried out in a targeted manner. First of all, in order to ensure the safety of the UAV design, we focus on the capabilities of the UAV body and build a risk identification, assessment, and modeling method such that the mission control parameters of the UAV can be determined. Then, the three-dimensional route planning algorithm based on the artificial potential fields algorithm is used to ensure the safe operation of the UAV online and in real time. At the same time, by adjusting the discriminant coefficient of potential risks in real time to deal with time-varying random disturbance encountered by the UAV, the resilience of the UAV 3D flight route planning can be improved. Finally, the effectiveness of the algorithm is verified by the simulation. The simulation results show that the REPARE algorithm can effectively solve the traditional route planning algorithm’s insufficiency in anti-disturbance. It is safer than a traditional A* route planning algorithm, and its running time is shorter than that of the traditional artificial potential field route planning algorithm. It solves the problems of local optimization, enhances the UAV’s ability to tolerate general uncertain disturbances, and eventually improves resilience of the system.

Highlights

  • Rotor UAVs have the advantages of low-state coupling and flexibility in space attitude, which greatly improves the work efficiency of the platform; they are favored by practitioners of high-altitude operations

  • The A* algorithm, represented by a small amount of calculations and fast speed, has difficulties ensuring the safe operation of the UAV in an environment involving disturbance

  • The anti-disturbance performance of the traditional route planning algorithm is not strong, and it will deviate from the expected route in the disturbance scenario, and it may collide with obstacles

Read more

Summary

Introduction

Rotor UAVs have the advantages of low-state coupling and flexibility in space attitude, which greatly improves the work efficiency of the platform; they are favored by practitioners of high-altitude operations. Even if the UAV is disturbed and shows a tendency to deviate from the route, it can be returned to the route When these algorithms are applied to the situations in which the disturbance intensity changes at any time and the change intensity span is large, they may cause insufficient or excessive correction, which will lead to security risks. On the basis of improving the A* algorithm and the artificial potential fields algorithm, this paper proposes the REPARE algorithm based on risk assessment, such that the UAV can operate independently and safely. In the face of disturbance, UAVs identify risks, assess the risks, counter the disturbance, and correct the route When facing obstacles, they dynamically avoid obstacles and plan routes. This paper analyzes the common disturbance scenarios of the rotor UAV and the force after the disturbance, and it realizes the resilience of the UAV’s navigation route through the parallel guarantee of two sets of mechanisms. AAss iiss sshhoowwnn iinn FFiigguurree 11,, wwhheenn tthhee ddiissttuurrbbaannccee ooccccuurrss,,tthheeUUAAVV iiddeennttiiffiieess ppootteennttiiaall sseeccuurriittyy rriisskkss aanndd uusseess tthhee UUAAVV’’ss ttwwoo--llaayyeerr sseeccuurriittyy pprrootteeccttiioonn mmeecchhaanniissmm;; tthhaatt iiss,, tthhee UUAAVV rreeffeerrsstotoitistsowown nphpyhsyicsailcaelnteintytiptyerpfoerrmfoarnmcaentcoedteotedrmetienremainreeaasorneaabsloensaebclueristeycruarnitgye rmanegcheamniescmhaannidsmtheanUdAtVheonUliAnVe roenall-itniemreemalo-tnimitoerimngonmiteocrhinagnimsme.chTahneisUmA.VTdheesUcrAibVesdthe-e sscarfiebteys btohuensdaaferytyabccoournddinargytoactchoerdminecghtaonitshme omfedcehtaenrmisminionfg daerteearmsoinnainbgle asarfeeatysornaanbglee, stahfeentydryannagme,icthaellny daydnjuasmtsictahlelyUaAdVjusrtosuttheepUlaAnVnirnoguatendplaonbnstiancgleanavdooidbsatnaccelepaavroaimdaentecres paaccraomrdeintegrstoacthcoerodninlingetoretahl-etiomnelinmeorneiatol-rtiinmgemmeochnaitnoirsimng, amndecshealencitssmth, aenadppserolepcrtisatteheroaupt-e prerosiplireiantceerpoluatnenrinesgilsietrnacteegpylafnonridnigffsetrreantet gleyvfeolsr odfifdfeisrteunrtblaenvceels; tohfudsi,stthuerbreasnicliee;ntcheuos,f tthhee rUesAilVieinsceenohfatnhceedU.AV is enhanced

UAV Risk Identification to Determine a Mechanism of Determining the
Dynamic Track Planning of Online Real-Time Monitoring Mechanism
Risk Assessment of Mechanisms for Determining Reasonable Security Scope
Disturbance Analysis of UAV in Wind and Rain
Disturbance Risk
Comprehensive Condition Discrimination Processor
Deployment Algorithms
Findings
Monte Carlo Simulation Verification
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call