An integrated approach to development of unmanned ground vehicle: design, analysis, implementation and suggestions

Year 2019, Volume: 34 Issue: 4, 1957 - 1974, 25.06.2019

Ömer Cihan Kıvanç , Tahir Eren Mungan Berkin Atila Gürkan Tosun

https://doi.org/10.17341/gazimmfd.571644

Cited By: 1

Abstract

In this study, an unmanned ground vehicle (UGV) has been developed, which has the ability to navigate to a
self-determined or unknown area, the ability of mapping, localization, trajectory detection and tracking,
detection of obstacles and finding a new path to avoid collisions with these obstacles. In an area without a
specific map, sketch or floor plan, UGV's autonomous driving capability in indoor and outdoor, has been
verified by the experiments. A general system block diagram and manufactured UGV are given in Figure A.

Purpose: The aim of the study is to develop the design and implementation of a UGV using an interdisciplinary approach and to determine the necessary algorithms and component selection criteria. Theory and Methods: In this study, the mechanical and electrical components of the UGV are determined and kinematic equations of the selected mechanical drive topology are obtained. The trajectory tracking algorithm is simulated in MATLAB/Simulink using the kinematic model of UGV. Also, hybrid filters have been developed to improve the performance of a low-precision GPS. Moreover, simultaneous localization and mapping (SLAM) algorithm is developed for autonomous driving in environments without GPS access. Results: The skidding and vibration of the mecanum wheels are compensated by the encoder, IMU and current sensor fusion. The disadvantages of a low-cost GPS have been minimized using the designed hybrid filters. Highperformance SLAM has been developed by including IMU and radar for HectorSLAM algorithm. Also, autonomous driving is performed using a heuristic path search and trajectory tracking algorithms in indoor and outdoor. Conclusion: The required phases, problems, solution techniques and results for UGV design are presented using an integrated approach in this study. The implementation details and the proof-of-concept design show that the design approach is suitable for use in the autonomous driving. 

Keywords

This work was supported by, the Scientific and, Technological Research, Council of Turkey, TÜBİTAK, funded project

İnsansız kara aracı geliştirmeye bütünleşik bir yaklaşım: tasarım, analiz, uygulama ve öneriler

Abstract

Akıllı
araç kavramının elektrikli araçlar ile ivme kazanması ve sonrasında otonom araç
teknolojilerine olan ilginin artmasıyla birlikte insansız kara aracı (İKA)
çalışmaları ve yatırımları hız kazanmaktadır. 
İnsansız kara araçları karmaşık bir yapıya ve teknolojiye sahip
olmalarına rağmen, kullanımlarıyla beraber birçok avantajı beraberlerinde
getirmektedirler. İnsana özgü özelliklere sahip olmamaları (uyku, yorgunluk,
sinir vb.), hızlı tepki verebilmeleri ve koşullara göre olasılıkları hesaplayıp
en doğru kararı seçebilmeleri İKA’ların en önemli avantajlarıdır. Yapılan
çalışmada, haritalandırma, konumlandırma, yol arama ve takip etme
kabiliyetlerine sahip bir İKA geliştirilmiştir. Belirli bir harita, kroki veya
kat planı bulunmayan bir arazide; İKA’nın açık ve kapalı alanda otonom sürüş
geliştirme kabiliyeti yapılan deneyler ile doğrulanmıştır. Çalışmada İKA
tasarımı için gereksinim duyulan aşamalar, problemler, çözüm teknikleri,
sonuçlar ve öneriler sistematik bir yaklaşım ile sunulmuştur.

Keywords

İnsansız kara araçları, yörünge takibi, eş zamanlı konum belirleme ve haritalandırma, kinematik modelleme, sezgisel yol arama

References

• 1. Bacik J., Durovsky F., Biro M., Kyslan K, Perdukova D., Padmanaban S., Pathfinder–development of automated guided vehicle for hospital logistics, IEEE Access, 5, 26892-26900, 2017.
• 2. Luettel T., Himmelsbach M., Wuensche H., Autonomous ground vehicles: concepts and a path to the future, Proc. IEEE, 100, 1831-1839, 2012.
• 3. Dickmanns E.D., Developing the sense of vision for autonomous road vehicles at UniBwM, Computer, 50 (12), 24-31, 2017.
• 4. Bimbraw K., Autonomous cars: Past, Present and Future a review of the Developments in the Last Century, the Present Scenario and the Expected Future of Autonomous Vehicle Technology, 12th International Conference on Informatics in Control, Automation and Robotics, Colmar, France, 21-23 July 2015.
• 5. Maxwell P., Larkin D., Lowrance C., Turning remote-controlled military systems into autonomous force multipliers, IEEE Potentials, 32 (6), 39-43, 2013.
• 6. Weiskircher T., Wang Q., Ayalew B., Predictive guidance and control framework for (semi-) autonomous vehicles in public traffic, IEEE Trans. Control Syst. Technol., 25 (6), 2034-2046, 2017.
• 7. Young S.H., Mazzuchi T.A., Sarkani S., A framework for predicting future system performance in autonomous unmanned ground vehicles, IEEE Trans. Syst. Man Cybern., 47 (7), 1192-1206, 2017.
• 8. Karlsson R., Gustafsson F., The future of automotive localization algorithms: available, reliable, and scalable localization: anywhere and anytime, IEEE Signal Process Mag., 34 (2), 60-69, 2017.
• 9. Broggi A., Buzzoni M., Debattisti S., Grisleri P., Laghi M.C., Medici P., Versari P., Extensive tests of autonomous driving technologies, IEEE Trans. Intell. Transp. Syst., 14 (3), 1403-1415, 2013.
• 10. Kilic A., Kapucu S., Design and construction of a modular reconfigurable robot module OMNIMO, Journal of the Faculty of Engineering and Architecture of Gazi University, 31 (3), 521-530, 2016.