Visual Odometry : Autonomous UAV Navigation using Optic Flow and Stereo

Visual odometry is vital to the future of mobile robotics. In this paper, we demonstrate a method that combines information from optic flow and stereo to estimate and control the current position of a quadrotor along a pre-defined trajectory. The absolute translation in 3D is computed by combining the optic flow measurements between successive frames and stereo-based height over ground. The current 3D position, as estimated from path integration of the incremental translations, is controlled in closed loop to follow the prescribed trajectory. The performance of the system is evaluated by measuring the error between the initial and final positions in closed circuits. This error is approximately 1.7% of the total path length.

[1]  Kostas Daniilidis,et al.  Monocular visual odometry in urban environments using an omnidirectional camera , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Mandyam V. Srinivasan,et al.  A Vision based system for attitude estimation of UAVS , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Mandyam V. Srinivasan,et al.  Robot Navigation by Visual Dead-Reckoning Inspiration From Insects , 1997, Int. J. Pattern Recognit. Artif. Intell..

[4]  Andrew Calway,et al.  Efficient visual odometry using a structure-driven temporal map , 2012, 2012 IEEE International Conference on Robotics and Automation.

[5]  F. Fraundorfer,et al.  Visual Odometry : Part II: Matching, Robustness, Optimization, and Applications , 2012, IEEE Robotics & Automation Magazine.

[6]  Clark F. Olson,et al.  Robust stereo ego-motion for long distance navigation , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[7]  Peter I. Corke,et al.  Experiments with Underwater Robot Localization and Tracking , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[8]  Navid Nourani-Vatani,et al.  Practical visual odometry for car-like vehicles , 2009, 2009 IEEE International Conference on Robotics and Automation.

[9]  Paul Newman,et al.  Outdoor SLAM using visual appearance and laser ranging , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[10]  Albert S. Huang,et al.  Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera , 2011, ISRR.

[11]  Mandyam V. Srinivasan,et al.  UAV attitude control using the visual horizon , 2010, ICRA 2010.

[12]  Kenzo Nonami,et al.  Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles , 2009, Robotics Auton. Syst..

[13]  Juho Kannala,et al.  A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  A. Favero,et al.  Italy , 1996, The Lancet.

[15]  Mandyam V. Srinivasan,et al.  A fast and adaptive method for estimating UAV attitude from the visual horizon , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Gaurav S. Sukhatme,et al.  Combined optic-flow and stereo-based navigation of urban canyons for a UAV , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  Marc Pollefeys,et al.  Autonomous Visual Mapping and Exploration With a Micro Aerial Vehicle , 2014, J. Field Robotics.

[18]  Davide Scaramuzza,et al.  SVO: Fast semi-direct monocular visual odometry , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[19]  Andreas Geiger,et al.  Visual odometry based on stereo image sequences with RANSAC-based outlier rejection scheme , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[20]  Larry H. Matthies,et al.  Two years of Visual Odometry on the Mars Exploration Rovers , 2007, J. Field Robotics.

[21]  Mandyam V Srinivasan,et al.  Honeybees as a model for the study of visually guided flight, navigation, and biologically inspired robotics. , 2011, Physiological reviews.

[22]  M. Powell.  The BOBYQA algorithm for bound constrained optimization without derivatives , 2009 .

[23]  Nicholas Roy,et al.  Stereo vision and laser odometry for autonomous helicopters in GPS-denied indoor environments , 2009, Defense + Commercial Sensing.

[24]  Mandyam V. Srinivasan,et al.  A method for the visual estimation and control of 3-DOF attitude for UAVs , 2011, ICRA 2011.

[25]  Navid Nourani-Vatani,et al.  Correlation‐based visual odometry for ground vehicles , 2011, J. Field Robotics.

[26]  Simon Lacroix,et al.  Vision-Based SLAM: Stereo and Monocular Approaches , 2007, International Journal of Computer Vision.

[27]  下越 弘子.  「International Congress of Mathematicians [ICM 2010]( 国際数学者会議)」に出展 , 2010 .

[28]  Matthew Garratt,et al.  Biologically inspired climbing with a hexapedal robot , 2008 .

[29]  James R. Bergen,et al.  Visual odometry for ground vehicle applications , 2006, J. Field Robotics.

[30]  Navid Nourani-Vatani,et al.  IMU aided 3D visual odometry for car-like vehicles , 2008, ICRA 2008.

[31]  Masatoshi Okutomi,et al.  Significance and attributes of subpixel estimation on area-based matching , 2003, Systems and Computers in Japan.

[32]  R. Richardson.  The International Congress of Mathematicians , 1932, Science.

[33]  G. Gerhart,et al.  Stereo vision and laser odometry for autonomous helicopters in GPS-denied indoor environments , 2009 .