AGV Navigation Based on AprilTags2 Auxiliary Positioning

Aiming at the problems of poor flexibility, complicated path maintenance and poor positioning performance in the current guidance technology of AGV, this paper designs and implements a new navigation system of automated guided vehicle (AGV) based on AprilTags2 auxiliary positioning. The system uses the Robot Operating System (ROS) as a platform to develop AGV navigation functions. The navigation system comprises two parts: the hardware and software layers. Firstly, hardware selection is performed after considering the actual requirements, performance, cost, and other factors in the hardware layer. Simultaneously, the AGV chassis and single-steering wheel walking mechanism are built to provide a stable and flexible operating platform for the software layer. Secondly, the software layer design includes two parts, namely the ROS navigation planning end and AprilTags2 detection. The ROS planning navigation end performs the design of four functional modules (i.e., AGV map construction, autonomous positioning, path planning, and path tracking), while the AprilTags2 detection part obtains the visual positioning pose of AGV by setting the AprilTags2 on each site and using the Kinect1 camera to detect. A more accurate AGV pose can be obtained by merging the former pose with the kinematic estimated pose. Finally, the two groups of positioning errors of the system before and after adding the AprilTags2 auxiliary positioning are tested and compared. The experimental results show that the navigation accuracy of the proposed system with AprilTags2 auxiliary positioning is significantly improved.

[1]  Edwin Olson,et al.  AprilTag 2: Efficient and robust fiducial detection , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[2]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[3]  Quan Quan,et al.  Pose Estimation for Multicopters Based on Monocular Vision and AprilTag , 2018, 2018 37th Chinese Control Conference (CCC).

[4]  Hugh F. Durrant-Whyte,et al.  An Autonomous Guided Vehicle for Cargo Handling Applications , 1995, ISER.

[5]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[6]  Edward D Lemaire,et al.  Fiducial Marker Approach for Biomechanical Smartphone-Based Measurements , 2019, 2019 3rd International Conference on Bio-engineering for Smart Technologies (BioSMART).

[7]  J. Rice Mathematical Statistics and Data Analysis , 1988 .

[8]  Edwin Olson,et al.  AprilTag: A robust and flexible visual fiducial system , 2011, 2011 IEEE International Conference on Robotics and Automation.

[9]  Sungshin Kim,et al.  Positioning Accuracy Improvement of Laser Navigation Using Unscented Kalman Filter , 2012, IAS.

[10]  Wei Xin Wang AGV Magnetic Sensor Data Acquisition System , 2015 .

[11]  Wolfgang Hess,et al.  Real-time loop closure in 2D LIDAR SLAM , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[12]  Zhang Jun,et al.  Research of AGV positioning based on the two-dimensional Code Recognition Method , 2015, 2015 International Conference on Logistics, Informatics and Service Sciences (LISS).

[13]  Thomas Bräunl,et al.  Cooperative multi-robot navigation, exploration, mapping and object detection with ROS , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[14]  Arbnor Pajaziti,et al.  SLAM – Map Building and Navigation via ROS , 2014 .

[15]  Song Li,et al.  On Adaptive Monte Carlo Localization Algorithm for the Mobile Robot Based on ROS , 2018, 2018 37th Chinese Control Conference (CCC).