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Autonomous navigation and indoor mapping for a service robot

Jovani Jimenez Builes
Universidad Nacional de Colombia, Colombia
Gustavo Acosta Amaya
Politécnico Colombiano Jaime Isaza Cadavid, Colombia
Julián López Velásquez
Politécnico Colombiano Jaime Isaza Cadavid, Colombia
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Abstract

Objective: Teach the operation of the Summit platform and the Powerball robot manipulator. Simultaneous Localization and Mapping (SLAM) is a quite common and interesting problem in mobile robotics. It is the basis of safe autonomous navigation of mobile robots and the entrance to new combined applications with a manipulator for instance. Methodology: In order to find a solution to the SLAM problem, the ROS middleware and the MRPT were selected. Autonomous navigation was tested using two methods, the MRPT navigation ROS package, which is a reactive navigation method based on Trajectory Parameter Space (TP-Space) transformations, and the ROS navigation stack, a standard for differential drive and holonomic wheeled robots. Results: To validate the advantages and disadvantages of both approaches, a mobile robot with strong kinematic constraints (Ackermann-steering-type) known as Summit was used. As an additional work, an application using the mobile robot Summit and a robotic manipulator (Powerball) was carried out, with the intention of picking and placing objects of the mobile robot, a widely spread application among service robotics, especially, in the area of industrial logistics. Conclusions: Finally, it is concluded that with the tests carried out with the robot, it was possible to demonstrate autonomous navigation, using the two
mentioned methods.

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References

  1. R. Megalingam, V. Naick, M. Motheram, J. Yannam, N. Gutlapalli & V. Sivanantham. "Robot operating system based autonomous navigation platform with human robot interaction". Telkomnika (Telecommunication Computing Electronics and Control), 21 (3), pp. 675 - 683, 2023. DOI: 10.12928/TELKOMNIKA.v21i3.24257.
  2. O. Chi, C. Chi, D. Gursoy & R. Nunkoo. "Customers’ acceptance of artificially intelligent service robots: The influence of trust and culture". International Journal of Information Management, 70, 2023. DOI: 10.1016/j.ijinfomgt.2023.102623.
  3. R. Megalingam, B. Tanmayi, G. Reddy, I. Krishna, G. Sree & S. Pai. "ROS-based GUI controlled robot for indoor mapping and navigation". Lecture Notes on Data Engineering and Communications Technologies, 58, pp. 283 - 294, 2021. DOI: 10.1007/978-981-15-9647-6_22.
  4. H. Durrant-Whyte & T. Bailey “Simultaneous localization and mapping (SLAM): Part I the essential algorithms”. IEEE Robotics Automation Magazine, 13(2):99110, 2006. DOI: 10.1109/MRA.2006.1638022.
  5. O. Hamzeh & A. Elnagar. “Localization and navigation of autonomous indoor mobile robots”. International Journal of Computing, Communications & Instrumentation Engg., vol. 2, pp. 228-233, 2015.
  6. N. Mohan, T. Shreekanth & B. Sandeep “Autonomous robot based on robot operating system (ROS) for mapping and navigation”. International Journal of Computer Science & Engineering Technology, vol. 6(7), pp. 449-457, 2015.
  7. S. Zaman, W. Slany & G. Steinbauer “ROS-based mapping, localization and autonomous navigation using a pioneer 3-DX robot and their relevant issues”. In: Saudi International Electronics, Communications and Photonics Conference (SIECPC), pp. 15, 2011. DOI: 10.1109/SIECPC.2011.5876943.
  8. E. Rodríguez. “Navegación autónoma de un robot móvil Summit”. Doctoral thesis. Universidad de Almería, España, 2015.
  9. J. Blanco. “Mobile Robot Programming Toolkit (MRPT)”. [Online]. Available: https://w3.ual.es/~jlblanco/software/ [Last access: 03 May 2023].
  10. A. Moniz & B. Krings Robots working with humans or humans working with robots? Searching for social dimensions in new human robot interaction in industry societies. Societies, vol. 6(3), pp. 123, 2016. DOI: 10.3390/soc6030023.
  11. H. Rasheed, Y. He, H. Khizar & H. Abbas. "Exploring consumer-robot interaction in the hospitality sector: Unpacking the reasons for adoption (or resistance) to artificial intelligence". Technological Forecasting and Social Change, 192, 2023. DOI: 10.1016/j.techfore.2023.122555
  12. G. Schunk. “Assembly and Operating Manual LWA 4P”. Schunk GmbH & Co. KG. Assembly and Operating Manual LWA 4P. [Online]. Available: https://schunk.com [Last access: 3 May 2023].
  13. T. Itsuka, M. Song, A. Kawamura & R. Kurazume “Development of ROS2-TMS: New software platform for informationally structured environment”. ROBOMECH Journal, 9(1), 2022. DOI: 10.1186/s40648-021-00216-2.
  14. H. Zhang, L. Yu & S. Fei. “Design of dual-LiDAR high precision natural navigation system”. IEEE Sensors Journal, 22(7), pp. 7231-7239, 2022. DOI: 10.1109/JSEN.2022.3153900.
  15. L. Contreras, T. Yamamoto, Y. Matsusaka & H. Okada “Towards general purpose service robots: World Robot Summit–Partner Robot Challenge”. Advanced Robotics, 2022. DOI: 10.1080/01691864.2022.2109428.
  16. Z. Wang, J. Peng, M. Dong, S. Song, S. Ding & Y. Liu. “Novel trajectory planning method based on double quaternion and Tau theory”. Lecture Notes in Electrical Engineering, pp. 482-491, 2022. DOI: 10.1007/978-981-16-6372-7_54.
  17. V. Raja, D. Talwar, A. Manchikanti & S. Jha. “Autonomous navigation for mobile robots with sensor fusion technology”. Lecture Notes in Mechanical Engineering, pp. 13-23, 2023. DOI: 10.1007/978-981-19-0561-2_2.
  18. N. Baslan, S. Heerklotz, S. Weber, A. Heerklotz, B. Hofig & J. Abu-Khalaf. “Navigation and vision system of a mobile robot”. In: Proceedings of the 19th International Conference on Research and Education in Mechatronics, Nro. 8421777, pp. 99-104, 2018. DOI:
  19. 1109/REM.2018.8421777.
  20. J. Blanco, J. González & J. Fernández. “Extending obstacle avoidance methods through multiple parameter-space transformations”. Autonomous Robots, vol. 24, pp. 2948, 2008. DOI: 10.1007/s10514-007-9062-7.
  21. H. Cheon, T. Kim, B. Kim, J. Moon & H. Kim. "Online waypoint path refinement for mobile robots using spatial definition and classification based on collision probability". IEEE Transactions on Industrial Electronics, 70 (7), pp. 7004 - 7013, 2023. DOI: 10.1109/TIE.2022.3203684.
  22. F. Dellaert, D. Fox, W. Burgard & S. Thrun. “Monte Carlo localization for mobile robots”. In: Proceedings - IEEE International Conference on Robotics and Automation, vol. 2, pp. 1322-1328, 1999. DOI: 10.1109/ROBOT.1999.772544.
  23. D. Coleman, I. Sucan, S. Chitta & N. Correll. “Reducing the barrier to entry of complex robotic software: A MoveIt! case study”. Journal of Software Engineering for Robotics, vol. 1(1), 2014.
  24. L. Yin, J. Liu, F. Zhou, M. Gao & M. Li. "Cost-based hierarchy genetic algorithm for service scheduling in robot cloud platform". Journal of Cloud Computing, 12 (1), Nro. 35, 2023. DOI: 10.1186/s13677-023-00395-w.
  25. L. Joseph. “Mastering ROS for robotics programming”. Second edition. Packt Publishing Ltd., USA, 2015.
  26. OMPL “The open motion planning library”. Technical report. Kavraki Lab, Department of Computer Science. [Online]. Available: https://ompl.kavrakilab.org/ [Last access: 03 May 2023].
  27. Movelt "Concepts". Technical report. PickNik Robotics. [Online]. Available: https://moveit.ros.org/documentation/concepts/ [Last access: 03 May 2023].
  28. R. Smits. “KDL: Kinematics and dynamics library”. Technical report. Orocos Kinematics and Dynamics. [Online]. Available: http://www.orocos.org/kdl [Last access: 03 May 2023].
  29. J. Pan, S. Chitta & D. Manocha. "FCL: A general purpose library for collision and proximity queries," 2012 IEEE International Conference on Robotics and Automation, Saint Paul, USA, pp. 3859-3866, 2012, DOI: 10.1109/ICRA.2012.6225337.
  30. J. Martínez Garcés y J. Barreto Fereira, “Modelo de planeación para la inversión tecnológica en centros de investigación universitarios”, Investigación e Innovación en Ingenierías, vol. 7, n.º 2, jul. 2019. DOI:10.17081/invinno.7.2.3448
  31. D. Fox. “KLD-sampling: Adaptive particle filters”. Advances in Neural Information Processing Systems, pp. 713-720, 2001.
How to Cite
[1]
J. Jimenez Builes, G. Acosta Amaya, and J. López Velásquez, “Autonomous navigation and indoor mapping for a service robot”, Investigación e Innovación en Ingenierías, vol. 11, no. 2, pp. 28–38, Sep. 2023.

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