Aided Navigation Techniques for Indoor and Outdoor Unmanned Vehicles

This paper presents design considerations of indoor and outdoor navigation techniques proposed for unmanned vehicles (UV). In this paper, we mainly investigate the use and the advantages of wireless sensor networks (WSNs) for indoor navigation, and Global Positioning System (GPS) for outdoor navigation. The system primarily uses laser range finder (LRF) measurements for indoor navigation, and is based on Extended Kalman Filter (EKF). For outdoor navigation the system uses Inertial Navigation System (INS) measurements. At periodical intervals the system integrates the measurements of an absolute sensor to improve estimations. The absolute sensor is a WSN interface for indoor navigation, and a GPS receiver for outdoor navigation. Simulation studies were conducted using Unified System for Automation and Robot Simulation (USARSim) and Player/Stage. The results of USARSim based simulations prove the advantages of integrating GPS measurements. Player/Stage based simulations show the advantages of integrating Received Signal Strength Indicator (RSSI) measurements obtained from WSN interfaces. In addition to the simulation studies, field tests with a custom-built Corobot autonomous robot platform will be realized to prove the effectiveness of the methods.

[1]  Jihua Huang,et al.  A Low-Order DGPS-Based Vehicle Positioning System Under Urban Environment , 2006, IEEE/ASME Transactions on Mechatronics.

[2]  Hugh F. Durrant-Whyte,et al.  A solution to the simultaneous localization and map building (SLAM) problem , 2001, IEEE Trans. Robotics Autom..

[3]  J.-E. Berg.  Building penetration loss along urban street microcells , 1996, Proceedings of PIMRC '96 - 7th International Symposium on Personal, Indoor, and Mobile Communications.

[4]  Stefano Carpin,et al.  USARSim: a robot simulator for research and education , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[5]  Chris Savarese.  LOCATIONING IN DISTRIBUTED AD-HOC WIRELESS SENSOR NETWORKS , 2001 .

[6]  Stefan B. Williams.  Efficient Solutions to Autonomous Mapping and Navigation Problems , 2009 .

[7]  Eduardo Nebot,et al.  Sensors Used for Autonomous Navigation , 1999 .

[8]  Gurkan Tuna,et al.  Communication related design considerations of WSN-aided Multi-Robot SLAM , 2011, 2011 IEEE International Conference on Mechatronics.

[9]  M.Q.-H. Meng,et al.  Particle filtering for WSN aided SLAM , 2008, 2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[10]  Jan M. Rabaey,et al.  Location in distributed ad-hoc wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[11]  S. Hara,et al.  Propagation characteristics of IEEE 802.15.4 radio signal and their application for location estimation , 2005, 2005 IEEE 61st Vehicular Technology Conference.