Humanoid robot localisation using stereo vision

This paper reports on the application of stereo vision localisation estimation techniques to a humanoid robot. Stereo vision has been used to localise wheeled robots with some success. Humanoid mounted stereo vision systems produce very jerky video sequences when the robot is walking. This can make the localisation task more problematic, especially when combined with the noisy nature of stereo depth, the 6DOF of camera motion, the difficulty to produce an accurate odometry estimate, and the desire to use dense stereo depth maps. Here, we apply established 2D localisation techniques to a humanoid robot using dense stereo vision depths maps and robot odometry

[1]  Masayuki Inaba,et al.  A Fast Generation Method of a Dynamically Stable Humanoid Robot Trajectory with Enhanced ZMP Constra , 2000 .

[2]  Don Ray Murray,et al.  Using Real-Time Stereo Vision for Mobile Robot Navigation , 2000, Auton. Robots.

[3]  Satoshi Kagami,et al.  Design and Implementation of Onbody Real-time Depthmap Generation System , 2000 .

[4]  Sebastian Thrun,et al.  Bayesian Landmark Learning for Mobile Robot Localization , 1998, Machine Learning.

[5]  Andrew J. Davison,et al.  Real-time simultaneous localisation and mapping with a single camera , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[6]  Wolfram Burgard,et al.  Estimating the Absolute Position of a Mobile Robot Using Position Probability Grids , 1996, AAAI/IAAI, Vol. 2.

[7]  Hugh F. Durrant-Whyte,et al.  Mobile robot localization by tracking geometric beacons , 1991, IEEE Trans. Robotics Autom..

[8]  Satoshi Kagami,et al.  Stereo vision and sonar sensor based view registration for 2.5 dimensional map generation , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[9]  Uwe D. Hanebeck,et al.  Perception errors in vision guided walking: analysis, modeling, and filtering , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[10]  Bernhard Schölkopf,et al.  Learning View Graphs for Robot Navigation , 1997, AGENTS '97.

[11]  Bernhard Schölkopf,et al.  Learning view graphs for robot navigation , 1997, AGENTS '97.

[12]  David W. Murray,et al.  Mobile Robot Localisation using Active Visual Sensing , 1998 .

[13]  K. Nagasaka,et al.  Stabilization of Dynamic Walk on a Humanoid Using Torso Position Compliance Control , 1999 .

[14]  Klaus H. Strobl,et al.  Task-Oriented and Situation-Dependent Gaze Control for Vision Guided Humanoid Walking , 2003 .

[15]  Patric Jensfelt,et al.  Approaches to Mobile Robot Localization in Indoor Environments , 2001 .

[16]  Masayuki Inaba,et al.  Memory-Based Navigation using Omni-View Sequence , 1998 .

[17]  Masayuki Inaba,et al.  Gyro Sensor based Compensation Method of Hip Joint Deformation for Stable Walking , 2002 .

[18]  K. Nishiwaki Humanoid 'JSK-H7' : Research Platform for Autonomous Behavior and Whole Body Motion , 2002 .

[19]  Satoshi Kagami,et al.  Revising Stereo Vision Maps in Particle Filter Based SLAM using Localisation Condence and Sample History , 2004 .

[20]  Wolfram Burgard,et al.  Monte Carlo localization for mobile robots , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[21]  James J. Little,et al.  σMCL: Monte-Carlo Localization for Mobile Robots with Stereo Vision , 2005, Robotics: Science and Systems.

[22]  Alexander Zelinsky,et al.  Accurate local positioning using visual landmarks from a panoramic sensor , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[23]  Masayuki Inaba,et al.  Design and implementation of software research platform for humanoid robotics: H6 , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[24]  Masayuki Inaba,et al.  Online generation of humanoid walking motion based on a fast generation method of motion pattern that follows desired ZMP , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.