A Novel Control and Monitoring Interface Design for ROS Based Mobile Robots

Year 2024, , 496 - 509, 26.01.2024

Bilal Gürevin , Muhammed Yıldız , Furkan Gültürk , İhsan Pehlivan , Fatih Çalışkan , Barış Boru , Mustafa Zahid Yıldız

https://doi.org/10.29130/dubited.1214278

Abstract

In this study, an interface design was carried out in order to provide convenience to the user in the control and monitoring of the Robot Operating System (ROS) based autonomous mobile robot (AMR). Qt Designer and Python were used in the interface design. Thanks to the designed interface, autonomous and manual control of AMR was provided. Using the gmapping algorithm, the environment in the virtual world was mapped and transformed into a picture in .png format and visualized in the interface. The location information from the ROS was transferred to the said picture and the instant tracking of the AMR was done via the interface. It was shown which algorithm is used locally and globally at that moment. While in autonomous mode, the vehicle was provided to move to the previously recorded point. The total distance and time spent by the AMR while moving between two points were also calculated by the interface. The location (x, y, z) and orientations (x, y, z, w) of the previously recorded station were monitored from the stop list. On the other hand, the position (x, y, z) and orientation (x, y, z, w) information of the AMR could be followed as real time via the interface. In this way, when the AMR reaches the goal station, the time elapsed between two points, the transportation distance, settlement information such as the location and orientation of the vehicle can be tracked and be compared via the interface.

Keywords

AMR, GUI, Path Planning, PyQt

Supporting Institution

Sakarya Uygulamalı Bilimler Üniversitesi, Bilimsel Araştırma Projeleri Koordinatörlüğü, TÜBİTAK

Project Number

BAP(075-2022), TUBITAK 2244 (118C142 )

Thanks

This study was obtained from the PhD project of SUBU, numbered 075-2022, named "Path Planning with Meta-Heuristic Algorithms in Autonomous Mobile Robots and Designing a New Mobile Robot" supported by BAP. It was also supported within the scope of TUBITAK-2244 project numbered 118C142.

ROS Tabanlı Mobil Robotlar İçin Yeni Bir Kontrol ve Görüntüleme Arayüz Tasarımı

Abstract

Bu çalışmada, Robot İşletim Sistemi (ROS) tabanlı otonom mobil robotun (AMR) kontrolünde ve izlenmesinde kullanıcıya kolaylık sağlamak amacıyla bir arayüz tasarımı gerçekleştirilmiştir. Arayüz tasarımında Qt Designer ve Python kullanılmıştır. Tasarlanan arayüz sayesinde AMR'nin otonom ve manuel kontrolü sağlanmıştır. Gmapping algoritması kullanılarak sanal dünyadaki ortam haritalanarak .png formatında resme dönüştürülerek arayüzde görselleştirilmiştir. ROS'tan gelen konum bilgisi söz konusu resme aktarılmış ve arayüz üzerinden AMR'nin anlık takibi yapılmıştır. Lokal ve global olarak o an hangi algoritmanın kullanıldığı gösterilmiştir. Otonom modda iken aracın önceden kaydedilen noktaya hareket etmesi sağlanmıştır. AMR'nin iki nokta arasında hareket ederken aldığı toplam mesafe ve süre de arayüz tarafından hesaplanmıştır. Durak listesinden daha önce kaydedilen istasyonun konumu (x, y, z) ve yönleri (x, y, z, w) takip edilebilmiştir. Öte yandan AMR'nin konum (x, y, z) ve yön (x, y, z, w) bilgileri arayüz üzerinden gerçek zamanlı olarak takip edilebilmiştir. Bu sayede AMR hedef istasyona ulaştığında, iki nokta arasında geçen süre, ulaşım mesafesi, aracın konumu, yönü gibi yerleşim bilgileri arayüz üzerinden takip edilip karşılaştırılabilmiştir.

Keywords

ROS, Yol Planlama, Arayüz Tasarımı, PyQt

Project Number

BAP(075-2022), TUBITAK 2244 (118C142 )

References

• [1] E.T. Baek and D.Y. Im, “ROS-Based Unmanned Mobile Robot Platform for Agriculture,” Appl. Sci., vol. 12, no. 9, p. 4335, 2022.
• [2] P. Karpyshev, V. Ilin, I. Kalinov, A. Petrovsky, and D. Tsetserukou, “Autonomous Mobile Robot for Apple Plant Disease Detection based on CNN and Multi-Spectral Vision System,” 2021.
• [3] J. Kriegel, C. Rissbacher, L. Reckwitz, and L. Tuttle-Weidinger, “The requirements and applications of autonomous mobile robotics (AMR) in hospitals from the perspective of nursing officers,” Int. J. Healthc. Manag., 2021.
• [4] M. Law et al., “Case studies on the usability, acceptability and functionality of autonomous mobile delivery robots in real-world healthcare settings,” Intell. Serv. Robot., vol. 14, no. 3, 2021.
• [5] C. Liu, J. Tan, H. Zhao, Y. Li, and X. Bai, “Path planning and intelligent scheduling of multi-AGV systems in workshop,” 2017.
• [6] H. Y. Zhang, W. M. Lin, and A. X. Chen, “Path planning for the mobile robot: A review,” Symmetry (Basel)., 2018. 509
• [7] C. Secchi, R. Olmi, F. Rocchi, and C. Fantuzzi, “A dynamic routing strategy for the traffic control of AGVs in automatic warehouses,” in Proceedings - IEEE International Conference on Robotics and Automation, 2015.
• [8] Y. Dongyong, C. Jinyin, N. Matsumoto, and Y. Yamane, “Multi-robot path planning based on cooperative co-evolution and adaptive CGA,” 2006.
• [9] J. K. Goyal and K. S. Nagla, “A new approach of path planning for mobile robots,” 2014.
• [10] B. Park, J. Choi, and W. K. Chung, “An efficient mobile robot path planning using hierarchical roadmap representation in indoor environment,” 2012.
• [11] O. Aslan and A. Yazici, “Conflict-Free Route Planning for Autonomous Transport Vehicle,” 2020.
• [12] Z. B. Garip, D. Karayel, S. S. Ozkan, and G. Atali, “Path planning for multiple mobile robots using A* algorithm,” Acta Phys. Pol. A, vol. 132, no. 3, pp. 685–688, 2017.
• [13] G. Atalı, I. Pehlivan, B. Gürevin, and H. I. Seker, “Chaos in metaheuristic based artificial intelligence algorithms: A short review,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 29, no. 3. 2021.
• [14] M. Y. Yıldırım and R. Akay, “Mobil Robotların Yol Planlamasında Doğrusallığın İncelenmesi,” Eur. J. Sci. Technol., 2021.
• [15] M. Y. Yıldırım and A. Rüştü, “A Comparative Study of Optimization Algorithms for Global Path Planning of Mobile Robots,” Sak. Univ. J. Sci., vol. 25, no. 2, pp. 417–428, 2021.
• [16] R. Wiki, http://wiki.ros.org/dwa_local_planner; 2022 [accessed 28 August 2022]
• [17] R. Wiki, http://wiki.ros.org/global_planner; 2022 [accessed 28 August 2022]
• [18] C. Z. Looi and D. W. K. Ng, “A Study on the Effect of Parameters for ROS Motion Planer and Navigation System for Indoor Robot,” Int. J. Electr. Comput. Eng. Res., vol. 1, no. 1, 2021.
• [19] B. Cybulski, A. Wegierska, and G. Granosik, “Accuracy comparison of navigation local planners on ROS-based mobile robot,” 2019.
• [20] S. Karakaya and H. Ocak, “Açısal Duruş Kontrolü Destekli Özgün bir Dinamik Pencere Yaklaşımı,” Bilecik Şeyh Edebali Üniversitesi Fen Bilim. Derg., vol. 7, no. 1, 2020.
• [21] P. Marin-Plaza, A. Hussein, D. Martin, and A. De La Escalera, “Global and Local Path Planning Study in a ROS-Based Research Platform for Autonomous Vehicles,” J. Adv. Transp., vol. 2018.
• [22] M. M. Moslemi and M. Sadedel, “Behavior Control and Navigation of Two-Wheeled Robot Using ROS-Gazebo,” in 2022 8th International Conference on Control, Instrumentation and Automation (ICCIA), 2022, pp. 1–6.
• [23] P. Xu, N. Wang, S. L. Dai, and L. Zuo, “Motion planning for mobile robot with modified BIT* and MPC,” Appl. Sci., vol. 11, no. 1, 2021.