Localization and Navigation of a Climbing Robot Inside a LPG Spherical Tank Based on Dual-LIDAR Scanning of Weld Beads

Mobile robot localization is a classical problem in robotics and many solutions are discussed. This problem becomes more challenging in environments with few and/or none landmarks and poor illumination conditions. This article presents a novel solution to improve robot localization inside a LPG spherical tank by robot motion of detected weld beads. No external light source and no easily detectable landmarks are required. The weld beads are detected by filtering and processing techniques applied to raw signals from the LIDAR (Light Detection And Ranging) sensors. A specific classification technique—-SVM (Support Vector Machine)—is used to sort data between noises and weld beads. Odometry is determined according to robot motion in relation with the weld beads. The data fusion of this odometry with another measurements is performed through Extended Kalman Filter (EKF) to improve the robot localization. Lastly, this improved position is used as input to the autonomous navigation system, allowing the robot to travel through the entire surface to be inspected.

[1]  F. Neves,et al.  Adhesion Force Control and Active Gravitational Compensation for Autonomous Inspection in LPG Storage Spheres , 2012, 2012 Brazilian Robotics Symposium and Latin American Robotics Symposium.

[2]  Andreu Corominas Murtra,et al.  IMU and cable encoder data fusion for in-pipe mobile robot localization , 2013, 2013 IEEE Conference on Technologies for Practical Robot Applications (TePRA).

[3]  Prabir Barooah,et al.  Error growth in position estimation from noisy relative pose measurements , 2013, Robotics Auton. Syst..

[4]  Philipp Koch,et al.  3D Multi-Sensor Data Fusion for Object Localization in Industrial Applications , 2014, ISR 2014.

[5]  John J. Leonard,et al.  Robust real-time visual odometry for dense RGB-D mapping , 2013, 2013 IEEE International Conference on Robotics and Automation.

[6]  Henry Leung,et al.  Mobile robot localization using odometry and kinect sensor , 2012, 2012 IEEE International Conference on Emerging Signal Processing Applications.

[7]  Weihe Guan,et al.  Present Status of Inspection Technology and Standards for Large-Sized In-Service Vertical Storage Tanks , 2011 .

[8]  S. Hiremath,et al.  Laser range finder model for autonomous navigation of a robot in a maize field using a particle filter , 2014 .

[9]  Michal Reinstein,et al.  Evaluation of the EKF-Based Estimation Architectures for Data Fusion in Mobile Robots , 2015, IEEE/ASME Transactions on Mechatronics.

[10]  Joachim Hertzberg,et al.  An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments , 2003, Robotics Auton. Syst..

[11]  Hang Dong,et al.  Lighting-Invariant Visual Odometry using Lidar Intensity Imagery and Pose Interpolation , 2012, FSR.

[12]  Mamoun F. Abdel-Hafez,et al.  Estimating Vehicle State by GPS/IMU Fusion with Vehicle Dynamics , 2013, 2013 International Conference on Unmanned Aircraft Systems (ICUAS).

[13]  Daniel Schwarz,et al.  Vehicle localization using cooperative RF-based landmarks , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[14]  Linlin Zhu,et al.  A Small and Lightweight Autonomous Laser Mapping System without GPS , 2013, J. Field Robotics.

[15]  Truong Q. Nguyen,et al.  An integrated stereo visual odometry for robotic navigation , 2014, Robotics Auton. Syst..

[16]  Veerachai Malyavej,et al.  Indoor robot localization by RSSI/IMU sensor fusion , 2013, 2013 10th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[17]  Paolo Dario,et al.  A Miniaturized Mechatronic System Inspired by Plant Roots for Soil Exploration , 2011, IEEE/ASME Transactions on Mechatronics.

[18]  Guoqiang Fu,et al.  An Integrated Triangulation Laser Scanner for Obstacle Detection of Miniature Mobile Robots in Indoor Environment , 2011, IEEE/ASME Transactions on Mechatronics.

[19]  André Schneider de Oliveira,et al.  Navigation’s Stabilization System of a Magnetic Adherence-Based Climbing Robot , 2015, J. Intell. Robotic Syst..

[20]  Laurent Itti,et al.  Mobile robot navigation system in outdoor pedestrian environment using vision-based road recognition , 2013, 2013 IEEE International Conference on Robotics and Automation.