Development of an Omni Directional based Mobile Robot Navigation System using Optimized-Fuzzy Social Force Model

ANUGERAH WIBISANA, BIMA SENA BAYU DEWANTARA, DADET PRAMADIHANTO

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ABSTRAK

Membangun sebuah sistem navigasi pada mobile robot yang bergerak di ruang sosial perlu memperhatikan beberapa aspek krusial, seperti menghindari rintangan, menjaga arah hadap robot ke tujuan, dan mencapai tujuan dengan cepat. Penelitian ini bertujuan untuk mengembangkan sistem navigasi pada Omnidirectional mobile robot menggunakan Fuzzy-Social Force Model (FSFM). Social Force Model (SFM) mampu menggerakan robot ke tujuan sambil menghindari rintangan. Fuzzy Inference System (FIS) digunakan untuk menghasilkan gain adaptif sebagai salah satu parameter SFM agar respon SFM sesuai dengan masukan dari sensor lidar. Aturan FIS dioptimasi agar mendapatkan nilai optimal menggunakan Particle Swarm Optimization (PSO). Dari hasil percobaan, mobile robot mencapai tujuan lebih cepat dengan selisih 1.59 s dan nilai error heading robot lebih kecil 0.9261 dibandingkan FSFM tanpa optimasi.

Kata kunci: Sistem Navigasi, Mobile Robot, Fuzzy-Social Force Model, Optimasi, Particle Swarm Optimization

 

ABSTRACT

Building a navigation system on a mobile robot moves in social space needs to consider several crucial aspects, such as avoiding obstacles, keeping the robot facing the destination, and reaching the destination quickly. This study aims to develop a navigation system on an Omnidirectional mobile robot using the Fuzzy-Social Force Model (FSFM). The Social Force Model (SFM) guides the mobile robot to its destination while avoiding obstacles. The Fuzzy Inference System (FIS) produces adaptive gain as one of the SFM parameters so that the response of the SFM matches the data of the lidar sensor. The rule base of FIS is optimized to get the optimal value using Particle Swarm Optimization (PSO). From the experimental results, mobile robots reach the destination faster with a difference of 1.59 s and a minor error in robot heading of 0.9261 compared to FSFM without optimization.

Keywords: Navigation System, Mobile Robot, Fuzzy-Social Force Model, Optimization, Particle Swarm Optimization


Kata Kunci


Navigation System; Mobile Robot; Fuzzy-Social Force Model; Optimization; Particle Swarm Optimization

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Referensi


Afridi, M. M., & Usman, J. (2019). Control and Efficiency Analysis of Multi-Motion of Four Wheel Drive Omni-Directional Robot. 2019 International Conference on Robotics and Automation in Industry (ICRAI) ,(pp. 3–8).

Bellarbi, A., Kahlouche, S., Achour, N., & Ouadah, N. (2017). A social planning and navigation for tour-guide robot in human environment. Proceedings of 2016 8th International Conference on Modelling, Identification and Control (ICMIC), (pp. 622–627).

Dewantara, B. S. B., & Ariyadi, B. N. D. (2021). Adaptive Behavior Control for Robot Soccer Navigation Using Fuzzy-based Social Force Model. Smart Science, 9(1), 14–29.

Dewantara, B. S. B., & Miura, J. (2017). Generation of a socially aware behavior of a guide robot using reinforcement learning. Proceedings - 2016 International Electronics Symposium (IES), (pp. 105–110).

Ferrer, G., Garrell, A., & Sanfeliu, A. (2013). Robot companion: A social-force based approach with human awareness-navigation in crowded environments. IEEE International Conference on Intelligent Robots and Systems, 41(4), 1688–1694.

Gil, Ó., Garrell, A., & Sanfeliu, A. (2021). Social robot navigation tasks: Combining machine learning techniques and social force model. Sensors, 21(21), 7087.

Helbing, D., & Molnár, P. (1995). Social force model for pedestrian dynamics. Physical Review E, 51(5), 4282–4286.

Kivrak, H., Cakmak, F., Kose, H., & Yavuz, S. (2021). Social navigation framework for assistive robots in human inhabited unknown environments. Engineering Science and Technology, an International Journal, 24(2), 284–298.

Kuderer, M., & Burgard, W. (2014). An approach to socially compliant leader following for mobile robots. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8755, 239–248.

Majeed, S. M., Abed, I. A., & Alsafaar, A. A. (2021). Path Planning with Static and Dynamic Obstacles Avoidance Using Image Processing. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(8), 1-7.

Marini, F., & Walczak, B. (2015). Particle swarm optimization (PSO). A tutorial. Chemometrics and Intelligent Laboratory Systems, 149, 153–165.

Muallimi, H. M., Dewantara, B. S. B., Pramadihanto, D., & Marta, B. S. (2020). Human partner and robot guide coordination system under social force model framework using kinect sensor. IES 2020 - International Electronics Symposium: The Role of Autonomous and Intelligent Systems for Human Life and Comfort, (pp. 260–264).

Ratsamee, P., Mae, Y., Ohara, K., Takubo, T., & Arai, T. (2013). Human-robot collision avoidance using a modified social force model with body pose and face orientation. International Journal of Humanoid Robotics, 10(1), 1–24.

Rifqi, A. T., Dewantara, B. S. B., Pramadihanto, D., & Marta, B. S. (2021). Fuzzy Social Force Model for Healthcare Robot Navigation and Obstacle Avoidance. International Electronics Symposium 2021: Wireless Technologies and Intelligent Systems for Better Human Lives, IES 2021 - Proceedings, (pp. 445–450).

Shayestegan, M., & Marhaban, M. H. (2012). Mobile robot safe navigation in unknown environment. Proceedings - 2012 IEEE International Conference on Control System, Computing and Engineering (ICCSCE), (pp. 44–49).

Tamura, Y., Fukuzawa, T., & Asama, H. (2010). Smooth collision avoidance in human-robot coexisting environment. IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS), (pp. 3887–3892).

Abdalla, T. Y., & Abdulkareem, A. A. (2013). A PSO Optimized Fuzzy Control Scheme for Mobile Robot Path Tracking. International Journal of Computer Applications, 76(2), 11–17.

Yang, C. T., Zhang, T., Chen, L. P., & Fu, L. C. (2019). Socially-aware navigation of omnidirectional mobile robot with extended social force model in multi-human environment. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, (pp. 1963–1968).




DOI: https://doi.org/10.26760/elkomika.v10i4.961

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