Robot Localization in Water Pipes Using Acoustic Signals and Pose Graph Optimization

One of the most fundamental tasks for robots inspecting water distribution pipes is localization, which allows for autonomous navigation, for faults to be communicated, and for interventions to be instigated. Pose-graph optimization using spatially varying information is used to enable localization within a feature-sparse length of pipe. We present a novel method for improving estimation of a robot’s trajectory using the measured acoustic field, which is applicable to other measurements such as magnetic field sensing. Experimental results show that the use of acoustic information in pose-graph optimization reduces errors by 39% compared to the use of typical pose-graph optimization using landmark features only. High location accuracy is essential to efficiently and effectively target investment to maximise the use of our aging pipe infrastructure.

[1]  Jens T. Thielemann,et al.  Pipeline landmark detection for autonomous robot navigation using time-of-flight imagery , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[2]  Wolfram Burgard,et al.  Localization on OpenStreetMap data using a 3D laser scanner , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[3]  Mamoun F. Abdel-Hafez,et al.  Pipeline Inspection Gauge Position Estimation Using Inertial Measurement Unit, Odometer, and a Set of Reference Stations , 2016 .

[4]  Aboelmagd Noureldin,et al.  Enhanced MEMS SINS Aided Pipeline Surveying System by Pipeline Junction Detection in Small Diameter Pipeline , 2017 .

[5]  Maan El Badaoui El Najjar,et al.  A Road-Matching Method for Precise Vehicle Localization Using Belief Theory and Kalman Filtering , 2005, Auton. Robots.

[6]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[7]  Lihua Xie,et al.  Graph Optimization Approach to Range-based Localization , 2018 .

[8]  Hyun Myung,et al.  Concept Design for Mole-Like Excavate Robot and Its Localization Method , 2019, 2019 7th International Conference on Robot Intelligence Technology and Applications (RiTA).

[9]  Shigeki Sugano,et al.  Modeling and Simulation of FLC-based Navigation Algorithm for Small Gas Pipeline Inspection Robot , 2018, 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

[10]  Philip E. Gill,et al.  Practical optimization , 1981 .

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

[12]  John J. Leonard,et al.  Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age , 2016, IEEE Transactions on Robotics.

[13]  Evangelos E. Milios,et al.  Globally Consistent Range Scan Alignment for Environment Mapping , 1997, Auton. Robots.

[14]  Meng Wang,et al.  Micro-Inertial-Aided High-Precision Positioning Method for Small-Diameter PIG Navigation , 2019, Advances in Human and Machine Navigation Systems.

[15]  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).

[16]  Sebastian Thrun,et al.  The Graph SLAM Algorithm with Applications to Large-Scale Mapping of Urban Structures , 2006, Int. J. Robotics Res..

[17]  Dennis Krys,et al.  INS-Assisted Monocular Robot Localization , 2010 .

[18]  Fumitoshi Matsuno,et al.  Sound-based online localization for an in-pipe snake robot , 2016, 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR).

[19]  Frank Dellaert,et al.  Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing , 2006, Int. J. Robotics Res..

[20]  Sean R. Anderson,et al.  Robot mapping and localisation in metal water pipes using hydrophone induced vibration and map alignment by dynamic time warping , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[21]  Sean R. Anderson,et al.  PipeSLAM: Simultaneous localisation and mapping in feature sparse water pipes using the Rao-Blackwellised particle filter , 2017, 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[22]  Shugen Ma,et al.  Recognition of pathway directions based on nonlinear least squares method , 2015, 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[23]  Biao Chen,et al.  Autonomous Localization and Mapping Using a Single Mobile Device , 2016, ArXiv.

[24]  Wolfram Burgard,et al.  A Tutorial on Graph-Based SLAM , 2010, IEEE Intelligent Transportation Systems Magazine.

[25]  Liang Liu,et al.  Indoor Positioning Based on Bluetooth Low-Energy Beacons Adopting Graph Optimization , 2018, Sensors.

[26]  Sean Anderson,et al.  Acoustic Echo-Localization for Pipe Inspection Robots , 2020, 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).

[27]  Hyun Myung,et al.  Resilient Underground Localization Using Magnetic Field Anomalies for Drilling Environment , 2018, IEEE Transactions on Industrial Electronics.

[28]  Shugen Ma,et al.  Anisotropic shadow-based operation assistant for a pipeline-inspection robot using a single illuminator and camera , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[29]  Carlos Rizzo,et al.  Graph-Based Robot Localization in Tunnels Using RF Fadings , 2019, ROBOT.

[30]  Wolfram Burgard,et al.  G2o: A general framework for graph optimization , 2011, 2011 IEEE International Conference on Robotics and Automation.

[31]  Hyun Myung,et al.  Magnetic field constraints and sequence-based matching for indoor pose graph SLAM , 2015, Robotics Auton. Syst..

[32]  David Alejo,et al.  A Robust Localization System for Inspection Robots in Sewer Networks † , 2019, Sensors.

[33]  Yang Li,et al.  Simultaneous Localization and Mapping with Power Network Electromagnetic Field , 2018, MobiCom.

[34]  Ja Choon Koo,et al.  Map building method for urban gas pipelines based on landmark detection , 2013 .

[35]  Newton Maruyama,et al.  Estimation of trajectories of pipeline PIGs using inertial measurements and non linear sensor fusion , 2010, 2010 9th IEEE/IAS International Conference on Industry Applications - INDUSCON 2010.

[36]  Byung-Ju Yi,et al.  SLAM in indoor pipelines with 15mm diameter , 2008, 2008 IEEE International Conference on Robotics and Automation.

[37]  Naser El-Sheimy,et al.  A Novel Method to Enhance Pipeline Trajectory Determination Using Pipeline Junctions , 2016, Sensors.

[38]  Mohammad A. Jaradat,et al.  Inertial Navigation System of Pipeline Inspection Gauge , 2020, IEEE Transactions on Control Systems Technology.

[39]  Brett Browning,et al.  Visual mapping for natural gas pipe inspection , 2015, Int. J. Robotics Res..

[40]  Chen Wang,et al.  Kernel Cross-Correlator , 2017, AAAI.

[41]  P. Bonnifait,et al.  Enhancement of global vehicle localization using navigable road maps and dead-reckoning , 2008, 2008 IEEE/ION Position, Location and Navigation Symposium.

[42]  Vijay Kumar,et al.  RF odometry for localization in pipes based on periodic signal fadings , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[43]  Andreas Geiger,et al.  Map-Based Probabilistic Visual Self-Localization , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[44]  Stephen Marshall,et al.  A novel visual pipework inspection system , 2018 .

[45]  J. Navarro-Pedreño Numerical Methods for Least Squares Problems , 1996 .

[46]  Robert Harle,et al.  MSGD: Scalable back-end for indoor magnetic field-based GraphSLAM , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).