winner presentation templatewinner.ajou.ac.kr/publication/data/invited/20171129_ncw.pdf ·...

국방 NCW 포럼 특별세션

UAV 활용 무선통신 기술

2017. 11. 29

Jae-Hyun Kim

jkim@ajou.ac.kr

Wireless Internet aNd Network Engineering Research Lab.

http://winner.ajou.ac.kr

School of Electrical and Computer Engineering

Ajou University, Korea

Contents

Introduction

Research Trends for UAV-aided wireless communication

Research Interest

Conclusion

Introduction

UAV(Unmanned Aerial Vehicles)

Definition [1]

Aerial vehicles that do not carry a human operator can fly autonomously or be piloted remotely

Different types of aerial objects/systems [2]

Include drones(ex. quadcopter), HAP(High Altitude Platform), LAP(Low Altitude Platform), Balloons, etc

• HAP : 15 Km(altitude), 38 – 39.5 GHz (Frequency band - Global)

• LAP : between 200 m to 6 km

[1] Joint Publication 1-02, “DOD Dictionary of Military and Associated Terms.”

[2] W. Saad, “Wireless communications and networking with unmanned aerial vehicles,” in proc. MILCOM 2017, Baltimore, MD, USA, Oct, 2017[3] Airbus, “Zephyr, High Altitude Pseudo-Satellite”[4] Google, “Loon Project”, https://x.company/projects/loon/

<HAP(Zephyr)> <LAP(Predator)> <Balloon(Loon Project)>

<Drone>

Introduction

UAV application & market growth

Application

Agriculture, transport, monitoring, patrol,entertainment, search and rescue, communications, etc.

Market growth[5]

[5] HIS Markit, http://news.ihsmarkit.com/press-release/aerospace-defense-security/significant-global-demand-pushes-uav-sales-exceed-82-billio 5

Agriculture

Entertainment Transport

MonitoringCommunication※ CAGR(Compound Annual Growth Rate)

Introduction

UAV-aided Wireless Communication

Functions of UAV in wireless communication

Communication among UAVs

• FANET(Flying ad-hoc Network), UAV swarm

Communication relay nodes

• Connect disconnected MANET(Mobile ad hoc network) clusters

Network gateway

• Connectivity to backbone networks, Internet, etc.

Advantage

Rapid placement

Flexible and scalable deployment

Coverage expansion

Low-cost operation

[6] I. Jawahr, N. Mohamed, J. A. Jaroodi, D. P. Agrawal, S. Zhang, “Communication and networking of UAV-based Systems: Classification and associated architectures,” Journal of Network and Computer Application, vol. 84, pp. 93-108, Apr. 2017 6

[7] KT, https://corp.kt.com/html/biz/services/trial.html [8] AT&T, “When COWs Fly: AT&T sending LTE Signals from drone,” http://about.att.com/innovationblog/cows_fly[9] Verizon, http://www.verizon.com/about/news/first-responders-make-calls-and-send-text-messages-using-flying-cell-site[10] SKT, http://www.sktelecom.co.kr/advertise/press_detail.do?idx=4190

Case of UAV-aided Wireless Communication(Commercial)

Mobile base station

KT(2015)

AT&T(Flying COWs, 2017)

Verizon(Flying cell site, 2016)

NTT DoCoMo(2017)

PS-LTE(Public Safety LTE)

SKT(control, 2017)

KT(Traffic Control Platform, 2017-2021)

Introduction

<PS-LTE><SKT, PS-LTE>

[11] Google, Project Skybender, https://www.theguardian.com/technology/2016/jan/29/project-skybender-google-drone-tests-internet-spaceport-virgin-galactic[12] Intel, https://www.intel.com/content/www/us/en/drones/drone-applications/commercial-drones.html[13] China mobile, https://www.sdxcentral.com/articles/news/china-mobile-eyes-5g-enabled-drones-solve-network-latency/2016/08/[14] IBM Watson, https://www.ibm.com/watson/

Case of UAV-aided Wireless Communication(Commercial)

5G mobile communication

Google (Skybender project, 2016)

Facebook

China Mobile(2016)

UAV-based IoT platform

Intel(2016)

Introduction

Case of UAV-aided Wireless Communication(Military)

Integrated tactical Network

JALN(Joint Aerial Layer Network)

• DoD

MUSIC(Manned Unmanned System Integration Capability)

• US Army

Multi-layer UAV network

ASIMUT Project

• European Defence Agency(EU), THALES, Bordeaux Univ., Luxmbourg Univ., Fraunhofer IOSB, Fly-&-Sense

Introduction

<JALN>

[15] “Joint Concept for Command and Control of the Joint Aerial Layer Network”, Joint Chiefs of Staff, 2015.03[16] U.S Army, “Manned Unmanned Sytems Integration Capability: MUSIC”[17] ASIMUT, https://asimut.gforge.uni.lu/description.html

[18] ‘Office of Naval Research’, https://www.onr.navy.mil[19] ‘U.S. Departure of Defense,’ https://www.defense.gov

Case of UAV-aided Wireless Communication(Military)

UAV swarm

Perdix-micro UAV swarm

• Department of defense(USA), MIT

• Field Test : Oct. 2016

LOCOST program

• Office of Naval Research(USA)

• Field Test : Apr. 2015

Introduction

Design challenges of UAV-aided wireless communication

Ensuring reliable network connectivity

High mobility environment of UAV systems

• Sparsely and intermittently connected

Effective interference management techniques

Mobility of UAVs, the lack of fixed backhaul links and centralized control

• Interference coordination among the neighboring cells with UAV-enabled Aerial base station

Energy-aware UAV deployment and operation mechanism

Limit UAVs communication, computation, and endurance capabilities

• SWaP(size, weight and power) constraint

Effective resource management and security mechanism

Supporting safety-critical functions(ex. CNPC links)

• Stringent latency(real-time) and security requirements

11[20] Y. Zeng, R. Zhang, T. J. Lim, “Wireless Communications with unmanned aerial vehicles: opportunities and challenges,” IEEE Communication Magazine, vol. 54,

no. 5, pp. 36 – 42, May. 2016.

※ CNPC : Control and Non-payload Communication

A2G(Air-to-ground) Channel Model

A2G Channels typically include,• LoS(Line-of-Sight), NLoS(Non Line-of-Sight)

• Multi-path components

» Reflection, scattering, diffraction

A2G radio propagation over urban environment[21]

Excessive pathloss(𝜂𝑛)

Dominant components

• LoS : Strong Signal (exist with probability 𝑷)

• NLoS : Strong reflection, fading (exist with probability 1-𝑃)

the effect of small-scale fluctuations are not consider

[2] W. Saad, “Wireless communications and networking with unmanned aerial vehicles,” in proc. MILCOM 2017, Baltimore, MD, USA, Oct, 2017[21] A. A. Hourani, S. kandeepan, A. Jamalipour, “Modeling Air-to-Ground path loss for low altitude platforms in urban environments,” in proc.

Globecom 2014, Austin, TX, USA, Dec. 2014.[22] A. A. Hourani, S. Kandeepan, “Optimal LAP altitude for maximum coverage,” IEEE Wirel. Commun. Letters, vol. 3, no. 6, pp 569 – 572, Dec. 2014

LoS NLoS

LoS probability over urban environments[22]

Dependent

• Ratio of built-up land area to the total land area(𝛼)

• Mean # of buildings per unit area(𝛽)

• Building’s heights distribution(𝛾) according to Rayleigh

ITU recommendation document suggests

LoS probability approximation• A continuous function of elevation angle 𝜽

» Closed sigmoid function

» 𝑟 = ℎ/𝑡𝑎𝑛𝜃, ℎ𝑅𝑋 0, smooth for large values of ℎ14

[22] A. A. Hourani, S. Kandeepan, “Optimal LAP altitude for maximum coverage,” IEEE Wirel. Commun. Letters, vol. 3, no. 6, pp 569 – 572, Dec. 2014

• 𝑎, 𝑏 : constant that depend on the environment• 𝜃 : elevation angle

Antenna height

𝑚 = floor(r 𝛼𝛽 − 1)

※ FSPL : Free Space Path Loss

A2G(Air-to-ground) Channel Model : Cell Radius vs. LAP altitude

15[22] A. A. Hourani, S. Kandeepan, “Optimal LAP altitude for maximum coverage,” IEEE Wirel. Commun. Letters, vol. 3, no. 6, pp 569 – 572, Dec. 2014

*Urban environment

- PlMax : Maximum allowed pathloss

Shadowing model for HAP in built-up areas[23]

Additional Shadowing Loss

• The shadowing effects of buildings on NLoS Connections

Rician fading model

Small scale fading

• Presence of a strong LoS component

K-factor[24]

• NASA measured in a near-urban

environment for CNPC link

» C-band(5.06 GHz) : Avg. 27dB (Min. 12.3dB)

» L-band (968MHz) : Avg. 12.7dB (Min 5dB)

• 𝐿𝐹𝑆𝐿 : Free space loss• 𝐿𝑆 : random shadowing in dB • 𝜁𝐿𝑂𝑆 , 𝜁𝑁𝐿𝑂𝑆 : random component

[23] J. Holis, P. Pechac, “Elevation dependent shadowing model for mobile communications via high altitude platforms in built-up areas,” IEEE Trans. Antennas and propagation, vol. 56, no. 4, pp. 1078 – 1084, Apr. 2008.[24] D. W. Matolak, R. Sun, “Air-Ground channel characterization for unmanned aircraft systems: the near-urban environment,” in Proc. MILCOM 2015,

Tempa, FL, USA, Oct. 2015.

𝑝𝜉 𝑥 =𝑥

𝜎02 exp(

−𝑥2−𝜌2

2𝜎02 )𝐼0(

𝑥𝜌

𝜎02)

• 𝜎02 : Average multipath component power

• 𝜌 : LoS amplitude• 𝐼0 : Bessel function

UAV deployment

UAV deployment and path planning

UAV-aided cellular coverage application

• Main design problems to achieve maximum coverage

» The optimal UAV separations

» The optimal altitude

UAV deployment and Operation

Energy-efficient communication

• Aims to satisfy the communication requirement with the minimum energy expenditure on communication-related function

» Communication circuits, signal transmission, hovering time etc.

» Optimize the energy efficiency in 𝑏/𝐽(bit per Joule)

• Extensively studied for terrestrial communications

» IoT devices

[20] Y. Zeng, R. Zhang, T. J. Lim, “Wireless Communications with unmanned aerial vehicles: opportunities and challenges,” IEEE Communication Magazine, vol. 54, no. 5, pp. 36 – 42, May. 2016.

UAV deployment

Next generation tactical communication networks with space and aerial

Purpose

• Future military communication network target service proposal including Aerial communication relay after TICN power-up

Network architecture

• By considering traffic size, mission and communication system

» Satellite(commercial, MILSAT, etc)

» UAV(High capacity, Low capacity)

» Ground(TICN, Solider)

[25] 조준우, 오지훈, 이재문, 김동현, 김재현, “우주/공중 기반 기동통신망 핵심기술, “한국통신학회지(정보와 통신), 제 33권 11호, pp. 65 – 72, 2016년 11월

UAV deployment

Next generation tactical communication networks with space and aerial

Analysis of traffic load amount of High Altitude UAV

• Worst/Best : most/least ground nodes are connected ground station which are failed

• # of Ground station failure : 1 6

Rank of High Altitude UAV according to traffic load

UAV deployment

Deployment strategies of multiple UAVs for optimal wireless coverage[25]

Purpose

• Investigate the optimal 3D deployment of multiple UAVs in order to maximize the downlink coverage performance

» Derive the downlink coverage probability for a UAV as a function of the UAV’s altitude and the antenna gain

» Propose an efficient deployment method which leads tothe maximum coverage performance while ensuring thatthe coverage areas of UAVs do not over lap

Coverage range of each UAV

20[26] M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage,” IEEE

Communications Letters, vol. 20, no. 8, pp. 1647-1650, Aug. 2016.

• 𝑟 : arbitrary range• 𝑃𝐶𝑂𝑉 : coverage probability (using LoS probability)

• 𝜃𝐵 : directional antenna half beamwidth

UAV deployment

Deployment strategies of multiple UAVs for optimal wireless coverage[25]

Maximize the total coverage

Approach Circle packing problem

[26] M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage,” IEEE

Communications Letters, vol. 20, no. 8, pp. 1647-1650, Aug. 2016.

R = 5km

Coverage vs. life time tradeoff : power, # of UAV, Altitude

UAV Resource Management

Bandwidth requirement

Reason

• Variety of data types and requirements in each UAV

• Assigned the bandwidth of the aircraft system to the CNPC links

Design consideration

• Maximizing bandwidth efficiency while meeting the demands

Hover and flight time constraint

Reason

• Limited on-board batteries, Flight regulation, weather conditions, etc.

Design consideration

• Minimizing flight time while meeting the demands

• Optimizing the service performance under flight time constraints

22[2] W. Saad, “Wireless communications and networking with unmanned aerial vehicles,” in proc. MILCOM 2017, Baltimore, MD, USA, Oct, 2017

Dynamic Resource Allocation Algorithm

Purpose

• Propose frame structure and the resource allocation algorithm which can maximize the network throughput

» Satisfy the minimum data rate requirement

23[27] H. R. Cheon, J. W. Cho, J. H. Kim, “Dynamic resource allocation algorithm of UAS by network environment and data requirement,” in proc.

ICTC 2017, jeju, Korea, 18 - 20, Oct. 2017.

자원 할당 알고리즘

Algorithm

• Critical : Control message

• Uncritical : video, voice, etc.

[27] H. R. Cheon, J. W. Cho, J. H. Kim, “Dynamic resource allocation algorithm of UAS by network environment and data requirement,” in proc. ICTC 2017, jeju, Korea, 18 - 20, Oct. 2017.

Performance result

• Compared Fixed unit time slot and Dynamic time slot

» Fixed : 1ms

Optimal transport theory for hover time optimization[28]

Purpose

• Maximize the average number of bit(data service) that is transmitted to the users under a fair resource allocation scheme

• The minimum average hover time that the UAVs need for completely servicing their ground users is derived

26[28] M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Wireless Commuinication using unmanned aerial vehicles (UAVs): optimal transport theory for

hover time optimization,” accepted in IEEE Trans. Wirel. Commun., 2017

Optimal cell partitioning for data service maximization with fair resource allocation

• Each cell partition is assigned to one UAV

Average data service at location (𝑥, 𝑦) ∈ 𝐴𝑖

• : cell partition• 𝑖 : # of UAVs • 𝑇𝑖 : effective transmission time of UAV 𝑖• 𝐵𝑖 : Bandwidth allocated to the user• 𝛾𝑖 : SINR

The load of each cell partition

Average # of users within

each cell partition

[28] M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Wireless Commuinication using unmanned aerial vhicles (UAVs): optimal transport theory for

• Using Kantorovich Duality Theorem

» minimizing total transportation costs

• Unconstrained maximization problem

Cost function depending on data service

• 𝜎0 : distributed ground users(standard deviation)

Average data service to users

Optimal hover time of UAV 𝑖 required to completely service the target area

• Control time which is not used for transmission(processing, computing, control signaling)

• 𝑁 : total # of users• 𝑢(𝑥, 𝑦) : load (in bits) of a user located at (𝑥, 𝑦)

• 𝐶𝑖𝐵𝑖 : Shannon capacity ( )

• 𝑔𝑖 : additional control time

effective data transmission time

Control time

Performance Analysis

UAV with underlaid D2D communications[27]

Purpose

• Deployment of an UAV as a flying base station used to provide on the fly wireless communications to a given geographical area is analyzed(coverage and rate performance)

Assumption

• Downlink users located uniformly in the cell with density 𝜆𝑑𝑢(# of users per 𝑚2)

• D2D users whose distribution follows homogeneous Poisson Point Process 𝜱𝑩 with density 𝜆𝑑(# of pairs per 𝑚2)

• A D2D receiver connects to its corresponding D2D transmitter pair located at a fixed distance away

• Interference from the UAV and other D2D transmitters

31[29] M. Mozaffari et. al, “Unmanned aerial vehicle with underlaid device-to-device communications: performance and tradeoffs,” IEEE Trans. Wirel. Commun.,

Feb. 2016

Interference

Impact of altitude on D2D coverage probability

• Coverage probability for D2D

• Coverage probability for Downlink user

Feb. 2016

Optimal UAV altitude

Average coverage probability for D2D(no interference between the UAV and the D2D

transmitter)

Interference(D2D)

• 𝜆𝑑 : D2D density• 𝑑0 : D2D transmitter location• 𝑃𝑑 : D2D transmit power• 𝑃𝑢 : UAV transmit power• 𝑋𝑢 : UAV-D2D distance

Impact of altitude on D2D coverage probability

• Average rate

» Sum rate

Feb. 2016

Assuming

Downlink user

Optimal UAV altitude

200m, 350m, 400m for

𝑑0 = 30m, 25m, 20m (D2D distance)

BLoS range extension with OPAL using UAVs

Purpose

• To extend the range of a tactical military network using UAVs

» UAVs autonomously optimize the network connectivity by relocating themselves

Optimization objective

• Placing the UAV radio relay is to improve the capacity of the network

• Using Shannon-Hartley theorem

» Derived network quality(Network Connection Level)

» The higher the SNR, the higher the capacity

34[30] K. P. Hui, D. Phillips, A. kekirigoda, “Beyond line-of-sight range extension with OPAL using autonomous unmanned aerial vehicles,” in proc. MILCOM

2017, Baltimore, MD, USA, Oct, 2017

Network connection Level

• 𝑖 : UAV flight path• 𝑇𝑘 : Time

• 𝑉 : Set of nodes

• 𝐸 : directed edges connecting two nodes(measuring its link quality as a SNR)

※ OPAL : self-healing communications network concept (autonomous system)

Scenario 1

• Two mobile ground node(node 1, node 2), UAV node

Node 1

Node 2

[30] K. P. Hui, D. Phillips, A. kekirigoda, “Beyond line-of-sight range extension with OPAL using autonomous unmanned aerial vehicles,” in proc. MILCOM 2017, Baltimore, MD, USA, Oct, 2017

Scenario 2

• Base Station(node 1) Mobile ground node(node 2), UAV node

Node 1

Node 2

Research Interest

UAV Wireless communication & Tactical Network

UAV 관련 MAC 프로토콜 개발 연구

TDMA 기반, 자가학습 관련 연구

차세대 대용량 다중접속 기술 연구(FNT-24)

주파수 효율 극대화 기법 및 대용량 변복조 기술을 통한 차세대 군 통합망 요소 기술 개발

• UAV 웨이브폼 기술연구

Conclusion

SummaryBackground and current status about UAV Definition of UAV

UAV application and market growth

Introduction to UAV-aided wireless communication Functions of UAV

• UAV-UAV, relay node, gateway

Advantages of UAV-aided wireless communication

Case of UAV-aided Wireless Communication(Commercial, Military)• Mobile base station, 5G communication, Integrated Network, UAV swarm, etc.

Design challenges of UAV-aided wireless communication Ensuring reliable network connectivity

Effective interference management techniques

Energy-aware UAV deployment and operation mechanism

Effective resource management and security mechanism

Conclusion

Summary

A2G Channel Model

• LoS probability

• Shadowing model for HAP in built-up areas

• Rician fading model with

UAV deployment

• Next generation tactical communication networks with space and aerial

• Deployment strategies of multiple UAVs for optimal wireless coverage

» to maximize the downlink coverage performance

• Bandwidth requirement

• Optimal transport theory for hover time optimization

Performance analysis

• Impact of altitude on coverage probability

• BLoS range extension with OPAL using UAVs 41

Reference

[1] Joint Publication 1-02, “DOD Dictionary of Military and Associated Terms.”[2] W. Saad, “Wireless communications and networking with unmanned aerial vehicles,” in proc. MILCOM 2017,

Baltimore, MD, USA, Oct, 2017[3] Airbus, “Zephyr, High Altitude Pseudo-Satellite”[4] Google, “Loon Project”, https://x.company/projects/loon/[5] HIS Markit, http://news.ihsmarkit.com/press-release/aerospace-defense-security/significant-global-demand-pushes-uav-sales-exceed-

82-billio[6] I. Jawahr, N. Mohamed, J. A. Jaroodi, D. P. Agrawal, S. Zhang, “Communication and networking of UAV-based Systems: Classification

and associated architectures,” Journal of Network and Computer Application, vol. 84, pp. 93-108, Apr. 2017[7] KT, https://corp.kt.com/html/biz/services/trial.html [8] AT&T, “When COWs Fly: AT&T sending LTE Signals from drone,” http://about.att.com/innovationblog/cows_fly[9] Verizon, http://www.verizon.com/about/news/first-responders-make-calls-and-send-text-messages-using-flying-cell-site[10] SKT, http://www.sktelecom.co.kr/advertise/press_detail.do?idx=4190[11] Google, Project Skybender, https://www.theguardian.com/technology/2016/jan/29/project-skybender-google-drone-tests-internet-

spaceport-virgin-galactic[12] Intel, https://www.intel.com/content/www/us/en/drones/drone-applications/commercial-drones.html[13] China mobile, https://www.sdxcentral.com/articles/news/china-mobile-eyes-5g-enabled-drones-solve-network-latency/2016/08/[14] IBM Watson, https://www.ibm.com/watson[15] “Joint Concept for Command and Control of the Joint Aerial Layer Network”, Joint Chiefs of Staff, 2015.03[16] U.S Army, “Manned Unmanned Sytems Integration Capability: MUSIC”[17] ASIMUT, https://asimut.gforge.uni.lu/description.html[18] ‘Office of Naval Research’, https://www.onr.navy.mil[19] ‘U.S. Departure of Defense,’ https://www.defense.gov

Reference

[20] Y. Zeng, R. Zhang, T. J. Lim, “Wireless Communications with unmanned aerial vehicles: opportunities and challenges,” IEEE Communication Magazine, vol. 54, no. 5, pp. 36 – 42, May. 2016.

[21] A. A. Hourani, S. kandeepan, A. Jamalipour, “Modeling Air-to-Ground path loss for low altitude platforms in urban environments,” in proc. Globecom 2014, Austin, TX, USA, Dec. 2014.

[22] A. A. Hourani, S. Kandeepan, “Optimal LAP altitude for maximum coverage,” IEEE Wirel. Commun. Letters, vol. 3, no. 6, pp 569 – 572, Dec. 2014

[23] J. Holis, P. Pechac, “Elevation dependent shadowing model for mobile communications via high altitude platforms in built-up areas,” IEEE Trans. Antennas and propagation, vol. 56, no. 4, pp. 1078 – 1084, Apr. 2008.

[24] D. W. Matolak, R. Sun, “Air-Ground channel characterization for unmanned aircraft systems: the near-urban environment,” in Proc. MILCOM 2015, Tempa, FL, USA, Oct. 2015.

[26] M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage,” IEEE Communications Letters, vol. 20, no. 8, pp. 1647-1650, Aug. 2016.

[28] M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, “Wireless Commuinication using unmanned aerial vehicles (UAVs): optimal transport theory for hover time optimization,” accepted in IEEE Trans. Wirel. Commun., 2017

[29] M. Mozaffari et. al, “Unmanned aerial vehicle with underlaid device-to-device communications: performance and tradeoffs,” IEEE Trans. Wirel. Commun., Feb. 2016

Thank you !

winner presentation templatewinner.ajou.ac.kr/publication/data/invited/20171129_ncw.pdf ·...

Documents

uav-memo-projekti, osa ii kevyiden miehittämättömien ilma...

aerial parts

polynomial chaos-based analysis of multirotor aerial ... ·...

k b weite anntenbewaffneten -...

k ] v - dialnet3 franke, u. e. drones, drone strikes, and us...

niversitÀ degli studi di napoli “federico ii” facoltÀ...

get into technology. are you… get into position. get...

response to reviews: a sampler for atmospheric volatile...

aerial bundle cable

autonomous transportation and deployment with aerial...

om fremtidig brug af ubemandede fly i det danske forsvar ·...

peter smith - bartonvale technologies - unmanned aerial...

formalveriﬁcationappliedtoattitudecontrol ... · unmanned...

aerial mastotuotteet - aerial mast products

einsatz uav in der vermessungsverwaltung der...

aerial vhf

remote sensing from unmanned aerial vehicles for 3d …

assessment of uav potential for bioacoustic …...studying...

unmanned vehicles -...

vehicles - ajsosteniblebcn.cat · vehicles indicador/s de...