Flocking Navigation in Swarm Robotics Jonas Hagge University of - - PowerPoint PPT Presentation

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Flocking Navigation in Swarm Robotics Jonas Hagge University of - - PowerPoint PPT Presentation

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MIN Faculty Department of Informatics Flocking Navigation in Swarm Robotics Jonas Hagge University of Hamburg Faculty of Mathematics, Informatics and Natural Sciences Department of Informatics Technical Aspects of Multimodal Systems 18.

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MIN Faculty Department of Informatics

Flocking Navigation in Swarm Robotics

Jonas Hagge

University of Hamburg Faculty of Mathematics, Informatics and Natural Sciences Department of Informatics Technical Aspects of Multimodal Systems

  • 18. November 2019
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Outline

Introduction Outdoor flocking and formation flight Results

  • 1. Introduction

Swarm Robotics Motivation Swarm Robotics Motivation Navigation

  • 2. Outdoor flocking and formation flight

Introduction Communication Algorithms Flocking and Formation

  • 3. Results

Conclusion Bibliography

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Swarm Robotics

Introduction Outdoor flocking and formation flight Results

◮ multiple autonomous robots ◮ non central coordination possible ◮ solve collective tasks

[Bay16] [dro] [rob]

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Swarm Robotics Motivation

Introduction Outdoor flocking and formation flight Results

◮ scalability ◮ flexibility ◮ robustness ◮ parallelism

[CPD+18, MDSD16]

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Use-Cases of Swarm Robotics

Introduction Outdoor flocking and formation flight Results

◮ Warehouse delivery (carrying objects) ◮ search and rescue (distributed map building) ◮ agriculuture (distributed sensing) ◮ Military (distributed map building and sensing) ◮ Airspace coordination

[CPD+18]

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Navigation Motivation

Introduction Outdoor flocking and formation flight Results

◮ each robot needs limited knowledge of environment ◮ group of animals is more effective for navigational tasks [DDWL08]

Real pigeons flying from R to H. [DDWL08]

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Paper

Introduction Outdoor flocking and formation flight Results

Paper Title: Outdoor flocking and formation flight with autonomous aerial robots published in: IROS 2014 Authors: G. Vásárhelyi, Cs. Virágh, G. Somorjai, N. Tarcai, T. Szörényi, T. Nepusz, T. Vicsek "All authors are with the Department of Biological Physics, Eötvös University, Budapest, Hungary" [VVS+14]

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Challenges

Introduction Outdoor flocking and formation flight Results

◮ still problems with autonomous flight maneuvers for single drones ◮ other flock members have to be detected ◮ delay in detection/communication ◮ weather

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Introduction

Introduction Outdoor flocking and formation flight Results

◮ GPS ◮ wireless communication ◮ using 10 Drones ◮ no central data processing unit

[VVS+14] The drone used for outdoor flocking and formation flight [VVS+14]

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Communication

Introduction Outdoor flocking and formation flight Results

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Short Range Repulsion

Introduction Outdoor flocking and formation flight Results

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Short Range Repulsion

Introduction Outdoor flocking and formation flight Results

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Middle range Velocity Alignment

Introduction Outdoor flocking and formation flight Results

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Middle range Velocity Alignment

Introduction Outdoor flocking and formation flight Results

length of arrow indicating speed

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Global positional constraints

Introduction Outdoor flocking and formation flight Results

◮ Flocking

◮ defined walls constrain movement ◮ walls implemented as virtual agents

◮ Formation Flights

◮ flying around global reference target ◮ for grid: heuristic for smallest circle

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Results

Introduction Outdoor flocking and formation flight Results

◮ 10 Drones

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Result Tracklogs Rectangle

Introduction Outdoor flocking and formation flight Results

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Result Tracklogs Circle

Introduction Outdoor flocking and formation flight Results

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Conclusion

Introduction Outdoor flocking and formation flight Results

◮ presented method used gps to get relative position, velocity, attitude information

◮ other systems outputting these informations could work with the same algorithms

◮ simulations showed larger numbers would be possible ◮ oscillation time could be improved ◮ real time os could help with delays

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[Bay16] Levent Bayındır. A review of swarm robotics tasks. Neurocomputing, 172:292–321, 2016. [CPD+18] Soon-Jo Chung, Aditya Avinash Paranjape, Philip Dames, Shaojie Shen, and Vijay Kumar. A survey on aerial swarm robotics. IEEE Transactions on Robotics, 34(4):837–855, 2018. [DDWL08] Gaia Dell’Ariccia, Giacomo Dell’Omo, David P Wolfer, and Hans-Peter Lipp. Flock flying improves pigeons’ homing: Gps track analysis of individual flyers versus small groups. Animal Behaviour, 76(4):1165–1172, 2008. [dro] Image of drone swarm.

https://spectrum.ieee.org/automaton/robotics/drones/ this-autonomous-quadrotor-swarm-doesnt-need-gps.

last accessed: 2019/11/12.

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[MDSD16] Gupta Mamta, Saxena Devika, Kumari Sugandha, and Kaur Dawinder. Issues and applications of swarm robotics. International Journal of Research in Engineering, Technology and Science, 6:1–5, 2016. [rob] Image of robocup.

https://guardian.ng/wp-content/uploads/2017/07/RoboCup.jpg. [VVS+14] Gábor Vásárhelyi, Cs Virágh, Gergo Somorjai, Norbert Tarcai, Tamás Szörényi, Tamás Nepusz, and Tamás Vicsek. Outdoor flocking and formation flight with autonomous aerial robots. In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3866–3873. IEEE, 2014.

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Short Range Repulsion

a→i

pot =

  • −D

j=i min(r1, r0 − |x→ij|) x→ij |x→ij|

if |x→ij| < r0 0 otherwise D → spring constant of a repulsive half-spring x→ij = x→j − x→i r0 → equilibrium distance r1 → upper treshold for repulsion

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Middle range Velocity Alignment

a→i

slip = Cfrict

  • j=i

v→ij (max(|x→ij|−(r0−r2),r1))2

Cfrict → viscous friction coefficient v→ij = v→j − v→i r0 → equilibrium distance r2 → constant slope around equilibrium distance r1 → lower threshold

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