Manufacturing Technology 2023, 23(4):504-512 | DOI: 10.21062/mft.2023.064

Mapping and Autonomous Obstacle Avoidance of Mobile Robot Based on ROS Platform

Peng Qian ORCID..., Naijia Xu ORCID..., Cunlong Fu ORCID..., Shudong Deng ORCID...
Anhui Sanlian University, Hefei 230601, China

With the progress of science and technology and the continuous development of robot technology, the performance and intelligence of robots are also constantly improving. It has been widely used in many fields such as life service, military, industrial production and so on. Among them, autonomous mobile is an important embodiment of intelligence. Therefore, it is necessary to solve the problem of robot real-time positioning and map building (SLAM). SLAM is the abbreviation of Simultaneous localization and mapping, which means "synchronous localization and mapping". It is mainly used to solve the problem of localization and mapping when robots move in unknown environments. This paper designs and implements a positioning and navigation system for mobile robots based on lidar in the environment of robot operating system (ROS). The system is based on the gamping algorithm of particle filter, so that robots can perform self-positioning and map building in strange environments. By studying the Rao-Blackwelized particle filter algorithm and enlarging the bandwidth of Kalman filter to increase its estimation accuracy, the filter was optimized. In the process of robot implementation of map construction and autonomous obstacle avoidance, the robot can conduct self-positioning and map building in unfamiliar environments by using the algorithm provided by the open source Gampping function package in the robot operating system (ROS).The navigation function package allows the robot to navigate independently and avoid obstacles with known maps of the environment. Finally, the simulation tool gazebo of the robot operating system (ROS) is used to build the simulation environment required for the experiment and simulate the real environment of the robot. Finally, the robot is equipped with lidar sensors to carry out experimental simulation, so that it can achieve the functions of self-positioning, map building, self-navigation and obstacle avoidance.

Keywords: Particle filter, Mobile robot, Mapping, Path planning
Grants and funding:

This paper was supported by the Research Fund Project of Anhui Sanlian University, Project Name: Research on SLAM algorithm optimization of autonomous mobile robots (NO.zjqr21002). Key scientific research project of Anhui Provincial Education Department, project name: Research on SLAM algorithm optimization of autonomous mobile robot (project approval number: 2022AH051980)

Received: May 25, 2023; Revised: August 9, 2023; Accepted: August 16, 2023; Prepublished online: August 30, 2023; Published: September 5, 2023  Show citation

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Qian P, Xu N, Fu C, Deng S. Mapping and Autonomous Obstacle Avoidance of Mobile Robot Based on ROS Platform. Manufacturing Technology. 2023;23(4):504-512. doi: 10.21062/mft.2023.064.
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    References

    1. QIAO YATONG. Research on storage AGV system design and path planning based on ROS platform, North China University, pp. 7-72022.5.
    2. LI HENG, YANG LIANG, ZENG BI, QI YUANHANG. Design and implementation of ROS based mobile robot simulation experiment platform, electronic design engineering, pp. 53-542022.7.
    3. JIANG CHAO. Research on ROS based autonomous exploration and real-time obstacle avoidance methods for mobile robots. Department of electronic engineering, Zhejiang University of Technology, pp. 13-142019.
    4. ČERNOHLÁVEK, V., SVOBODA, M., ŠTĚRBA, J., CHALUPA, M. & SAPIETA, M. 2020. Analytical and experimental solution of vibrations of a system of bound bodies. Manufacturing Technology, 20, 699-707. Go to original source...
    5. SHAO MINGSHENG, ZHANG SIWEI. Blind signal separation based on secondary fission particle swarm optimization. Piezoelectric and acoustooptic, vo1.34, No.1, pp. 159-160, 2012.
    6. WEN SHENGPING, HUANG PEIHUI. Design of embedded control system for laser guided mobile robot. Automation and instrumentation, pp. 25-26, 2018.
    7. ZHOU XIAOHUA, WU TAO, LI BO, SUN JIAHUI. Research on four wheel drive mobile robot based on ROS and Px4 flight control. Modern electronic technology, pp. 7-82022.
    8. SVOBODA, M., VAN DER KAMP, K., JELEN, K. & SAPIETA, M. 2019. Identification of Changes in Mechanical Properties of Human Axial System Due to Stress and Relaxation Regime. Manufacturing Technology, 19, 860-7. Go to original source...
    9. YE QIANGQIANG, ZHENG MINGKUI, QIU XIN. Implementation of indoor autonomous navigation mobile robot system based on ROS. Fuzhou University, vo1.41, No. 2, pp. 92-93, 2022.
    10. HU CHUNXU. Design and implementation of cloud robot platform based on ROS. Department of artificial intelligence and automation, Huazhong University of science and technology. pp. 6-37, 2015.
    11. ZHANG SAI. Research on path planning algorithm of indoor mobile robot based on ROS system. Department of control engineering, Tianjin University of Technology. pp. 22-232022.
    12. TIMKO, P., HOLUBJAK, J., BECHNÝ, V., NOVÁK, M., CZÁN, A. & CZÁNOVÁ, T. 2023. Surface Analysis and Digitization of Components Manufactured by SLM and ADAM Additive Technologies. Manufacturing Technology, 23, 127-34. Go to original source...
    13. GE WENYA, LI PING. Global dynamic path planning fusion algorithm for mobile robots. Journal of Huaqiao University (NATURAL SCIENCE EDITION), pp. 87-882022.
    14. XIONG AN, BIAN CHUNJIANG, ZHOU HAI, LIU CHENG. Simulation design of robot positioning and navigation system based on ROS. Electronic design engineering, pp. 189-190, 2018.
    15. CHENG LU. Research on ROS based mobile robot map construction and path planning technology, Anhui University of Engineering, pp. 9-102022.4.
    16. GERLICI, J., MUSIIKO, V., KOVAL, A., NIKOLAENKO, V., LAZARUK, J., LACK, T. & KRAVCHENKO, K. 2020. Experimental analysis of the universal continuous digging machine working processes. Manufacturing Technology, 20, 429-35. Go to original source...
    17. LI ZHIKUN. Research on path planning and map building methods of mobile robots, Anhui University of Engineering, pp. 42-432022.3.
    18. CHENG TIANMING, CHEN YUANDIAN, SU CHENGYUE, XU SHENG, YANG SHANGRU, LIU BA. Research on mobile robot obstacle map construction, Modern computer, pp. 38-432021 (20).
    19. ZHENG GUOXIAN, ZHANG LEI, ZHANG HUAXI. Autonomous exploration of robot indoor environment and map building method, Control engineering, pp. 1744-17452020.10.
    20. LENG BINGHAN, Research on path planning and autonomous obstacle avoidance of mobile robots, Harbin Engineering University, pp. 35-362021.5.
    21. BAISHI, Research on mobile robot map construction technology for unknown environment, Hebei University of technology, pp. 52-532022.3.
    22. YANG MINGHUI, WU YAO, ZHANG YONG, XIAO XIAOHUI. Autonomous obstacle avoidance strategy of mobile robots in indoor dynamic environment, Journal of Central South University (NATURAL SCIENCE EDITION). pp. 1833-18342019, 50 (08).

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