Abstract
Günümüzde pek çok karmaşık görev
için donanım ve çalışma hızı açısından hantal ve maliyetli robotik sistemler
kullanılmaktadır. Pahalı ve hantal bir robot yerine daha küçük ve basit
robotlardan oluşan sistemlerle aynı karmaşık görevleri yerine getirme konusunda
yapılan çalışmalar çoklu robotiği ortaya çıkarmıştır. Çoklu ajanlardan oluşan
sürülerin hareketi için ilk çözüm modeli Reynolds tarafından hazırlanan Boids
algoritmasıdır. Boids algoritması birleşme (cohesion), ayrılma (dispersion) ve
hizalanma (align) kurallarının oluşturduğu vektörlerin her ajan için birleştirilip
her ajana ayrı uygulanması olarak tanımlanmıştır. Diğer çalışmalardan farklı
olarak bu çalışmada bulanık-işbirlikli bir algoritma tasarlanarak hem akın hem
de düzen alma davranışlarının gerçekleştirilmesi amaçlanmıştır. Amaç
doğrultusunda birden fazla robotun bireysel, işbirlikli ve bulanık-işbirlikli
halde akın etmesi ve düzen alması incelenmiş ve türetilen bulanık-işbirlikli
algoritmanın başarımı sınanmıştır. Çalışmada sırasıyla, benzetim ortamında
kullanılan robot ve görev algoritmaları sunulmuş olup ardından benzetim
sonuçları verilmiştir. Elde edilen bulgulara göre tasarlanan Bulanık akın
algoritması, Boids algoritmasından daha kısa görev tamamlama süresi ve daha az
haberleşme tekrarı sağladığı görülmüştür.
References
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- C. W. Reynolds. “Steering behaviors for autonomous characters.” in Game developers conference. 1999. vol. 1999. pp. 763–782.
- H. H. Lund and L. Pagliarini. “Robot soccer with LEGO mindstorms.” in Robot Soccer World Cup. 1998. pp. 141–151.
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- Ö. Ahmet and M. Sinecen. “KLİMA SİSTEM KONTROLÜNÜN BULANIK MANTIK İLE MODELLEMESİ.” Pamukkale Üniversitesi Mühendis. Bilim. Derg.. vol. 10. no. 3. pp. 353–358. 2004.
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Abstract
Today, cumbersome and costly robotic systems are used
for many complex tasks in terms of hardware and operating speed. Instead, the
work on performing the same complex tasks as the systems consisting of smaller
and simpler robots reveals the multiple robotics, a sub-branch of robotics. The
first solution model for the multiple agents flocking behaviors is the Boids
algorithm prepared by Reynolds. The Boids algorithm is defined as the
combination of cohesion, dispersion and align rules for each agent and
application for individuals. Unlike other studies, a fuzzy-collaborative
algorithm was designed in this study and it was aimed to perform both flock and
formation behaviors. Within the scope of the aim; individual, cooperative and
fuzzy-collaborative flocking and formation of multiple robots were examined and
the performance of the fuzzy-cooperative algorithm was tested. In the study,
robot and task algorithms used in simulation environment are presented and
simulation results are given. According to the findings, the fuzzy flocking
algorithm is faster and requires less communication cycle than the Boids
algorithm.
References
- A. Ç. Seçkin. C. Karpuz. and A. Özek. “Feature matching based positioning algorithm for swarm robotics.” Comput. Electr. Eng.. 2016.
- L. Bayındır. “A review of swarm robotics tasks.” Neurocomputing. vol. 172. pp. 292–321. 2016.
- L. Bayindir and E. Şahin. “A review of studies in swarm robotics.” Turk. J. Electr. Eng. Comput. Sci.. vol. 15. no. 2. pp. 115–147. 2007.
- A. Ç. Seçkin. C. Karpuz. and A. Özek. “Sürü Robotiği.” presented at the UBMK’16 - Uluslararası Bilgisayar Bilimleri ve Mühendisliği Konferansı. Tekirdağ Turkey. 2016. pp. 414–419.
- S. Kloder and S. Hutchinson. “Path planning for permutation-invariant multirobot formations.” Robot. IEEE Trans. On. vol. 22. no. 4. pp. 650–665. 2006.
- A. I. Mourikis and S. I. Roumeliotis. “Performance analysis of multirobot cooperative localization.” Robot. IEEE Trans. On. vol. 22. no. 4. pp. 666–681. 2006.
- G. Vásárhelyi et al.. “Outdoor flocking and formation flight with autonomous aerial robots.” in Intelligent Robots and Systems (IROS 2014). 2014 IEEE/RSJ International Conference on. 2014. pp. 3866–3873.
- G. López-Nicolás. M. Aranda. and C. Sagüés. “Multi-robot Formations: One Homography to Rule Them All.” in ROBOT2013: First Iberian Robotics Conference: Advances in Robotics. Vol. 1. M. A. Armada. A. Sanfeliu. and M. Ferre. Eds. Cham: Springer International Publishing. 2014. pp. 703–714.
- M. Aranda. G. López-Nicolás. C. Sagüés. and Y. Mezouar. “Formation control of mobile robots using multiple aerial cameras.” IEEE Trans. Robot.. vol. 31. no. 4. pp. 1064–1071. 2015.
- M. J. Mataric. “Designing emergent behaviors: From local interactions to collective intelligence.” in Proceedings of the Second International Conference on Simulation of Adaptive Behavior. 1993. pp. 432–441.
- C. W. Reynolds. “Flocks. herds and schools: A distributed behavioral model.” ACM SIGGRAPH Comput. Graph.. vol. 21. no. 4. pp. 25–34. 1987.
- C. W. Reynolds. “Steering behaviors for autonomous characters.” in Game developers conference. 1999. vol. 1999. pp. 763–782.
- H. H. Lund and L. Pagliarini. “Robot soccer with LEGO mindstorms.” in Robot Soccer World Cup. 1998. pp. 141–151.
- N. Bouraqadi. A. Doniec. and E. M. de Douai. “Flocking-based multi-robot exploration.” in National conference on control architectures of robots. 2009.
- Ö. Ahmet and M. Sinecen. “KLİMA SİSTEM KONTROLÜNÜN BULANIK MANTIK İLE MODELLEMESİ.” Pamukkale Üniversitesi Mühendis. Bilim. Derg.. vol. 10. no. 3. pp. 353–358. 2004.
- Ç. Gençer and A. Coşkun. “Robust Speed Control of Permanent Magnet Synchronous Motors Using Adaptive Neuro Fuzzy Inference System Controllers.” Asian J. Inf. Technol.. vol. 4. no. 10. pp. 918–919. 2005.
- A. Coşkun and Y. Yılmaz. “Bone Age Assessment with Fuzzy Logic.”
- F. Bozkurt. A. Ç. Seçkin. and A. Coşkun. “Integration of IMU Sensor on Low-Cost EEG and Design of Cursor Control System with ANFIS.”
- I. L. Bajec. M. Mraz. and N. Zimic. Boids with a fuzzy way of thinking. Anaheim: ACTA Press. 2003.
- I. L. Bajec. N. Zimic. and M. Mraz. “Simulating flocks on the wing: the fuzzy approach.” J. Theor. Biol.. vol. 233. no. 2. pp. 199–220. 2005.
- Z. Wang and D. Gu. “Behaviour based fuzzy flocking systems.” in Fuzzy Systems Conference. 2007. FUZZ-IEEE 2007. IEEE International. 2007. pp. 1–6.
- X. Zhong and G. Cao. “Fuzzy boids using a dynamic weighting method based on Gauss circle.” in Control Conference (CCC). 2016 35th Chinese. 2016. pp. 7567–7571.
- E. Rohmer. S. P. Singh. and M. Freese. “V-REP: A versatile and scalable robot simulation framework.” in Intelligent Robots and Systems (IROS). 2013 IEEE/RSJ International Conference on. 2013. pp. 1321–1326.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Publication Date | December 1, 2019 |
| Submission Date | November 10, 2018 |
| Published in Issue | Year 2019 Volume: 22 Issue: 4 |
Cite
Cited By
Implementation of Collaborative Multi-Robot System Carrying Cargos Autonomously
Uluslararası Muhendislik Arastirma ve Gelistirme Dergisi
Emrah BUDAK
https://doi.org/10.29137/umagd.686123
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