The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Autonomous Driving Electric Vehicle for Logistics with a Robotic Arm

로봇팔을 지닌 물류용 자율주행 전기차 플랫폼 개발

  • Received : 2022.10.31
  • Accepted : 2022.12.03
  • Published : 2023.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, the development of an autonomous electric vehicle for logistics with a robotic arm is introduced. The manual driving electric vehicle was converted into an electric vehicle platform capable of autonomous driving. For autonomous driving, an encoder is installed on the driving wheels, and an electronic power steering system is applied for automatic steering. The electric vehicle is equipped with a lidar sensor, a depth camera, and an ultrasonic sensor to recognize the surrounding environment, create a map, and recognize the vehicle location. The odometry was calculated using the bicycle motion model, and the map was created using the SLAM algorithm. To estimate the location of the platform based on the generated map, AMCL algorithm using Lidar was applied. A user interface was developed to create and modify a waypoint in order to move a predetermined place according to the logistics process. An A-star-based global path was generated to move to the destination, and a DWA-based local path was generated to trace the global path. The autonomous electric vehicle developed in this paper was tested and its utility was verified in a warehouse.

Keywords

Acknowledgement

This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 171134144, Development of a self-driving electric vehicle platform that can be switched to the manned or unmanned for an integrated logistics robot)

References

  1. T. H. Lee, J. S. Huh, and J. H. Na, "Logistics Industry Outlook and Tasks in 2022," Monthly KOTI Magazine on Transport, vol. 286, pp. 30-37, 2021, [Online], https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11058301.  1058301
  2. J. Toledo, J. D. Pineiro, R. Arnay, D. Acosta, and L. Acosta, "Improving Odometric Accuracy for an Autonomous Electric Cart," Sensors, vol. 18, no. 1, 2018, DOI: 10.3390/s18010200. 
  3. S. J. Park and T. Yang, "A Study on Design of Intelligent Mobile Robot based on Localization Sensor for Unmanned Transport Logistics," Journal of KIIT, vol. 11, no. 9, pp. 7-13, 2013, [Online], https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArti View.kci?sereArticleSearchBean.artiId=ART001803226.  https://doi.org/10.14801/kiitr.2013.11.9.7
  4. S. H. Kim, J. M. Sim, Y. S. Park, and D. H. Jung, "LiDAR-Based Smart Logistics Robot," Symposium of the Korean Institute of communications and Information Sciences, pp. 995-996, 2021, [Online], https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11023013. 
  5. P. Polack, F. Altche, B. d'Andrea-Novel, and A. de La Fortelle, "The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?," IEEE Symposium on Intelligent Vehicle, Los Angeles, USA, 2017, DOI: 10.1109/IVS.2017.7995816. 
  6. H. Durrant-Whyte and T. Bailey, "Simultaneous localization and mapping (SLAM): Part I," IEEE Robotics & Automation Magazine, vol. 13, no. 2, pp. 99-110, 2006, DOI: 10.1109/MRA.2006.1638022. 
  7. M. Quigley, K. Conley, B. P. Gerkey, and J. Faust, "ROS: an open-source Robot Operating System," ICRA workshop on open source software, 2009, [Online], https://www.researchgate.net/publication/233881999_ROS_an_open-source_Robot_Operating_System. 
  8. B. L. E. A. Balasuriya, B. A. H. Chathuranga, B. H. M. D. Jayasundara, N. R. A. C. Napagoda, S. P. Kumarawadu, D. P. Chandima, and A. G. B. P. Jayasekara, "Outdoor robot navigation using Gmapping based SLAM algorithm," Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2016, DOI: 10.1109/MERCon.2016.7480175. 
  9. M.-A. Chung and C.-W. Lin, "An improved localization of mobile robotic system based on AMCL algorithm," IEEE Sensors Journal, vol. 22, no.1, pp. 900-908, 2022, DOI: 10.1109/JSEN.2021.3126605. 
  10. F. Duchon, A. Babinec, M. Kajan, P. Beno, M. Florek, T. Fico, and L. Jurisica, "Path planning with modified a star algorithm for a mobile robot," Procedia Engineering, vol. 96, pp. 59-69, 2014, DOI: 10.1016/j.proeng.2014.12.098. 
  11. M. Pittner, M. Hiller, F. Particke, L. Patino-Studencki, and J. Thielecke, "Systematic Analysis of Global and Local Planners for Optimal Trajectory Planning," ISR 2018; 50th International Symposium on Robotics, Munich, Germany, 2018, [Online], https://ieeexplore.ieee.org/document/8470582.