Towards hierarchical blackboard mapping on a whiskered robot

The paradigm case for robotic mapping assumes large quantities of sensory information which allow the use of relatively weak priors. In contrast, the present study considers the mapping problem for a mobile robot, CrunchBot, where only sparse, local tactile information from whisker sensors is available. To compensate for such weak likelihood information, we make use of low-level signal processing and strong hierarchical object priors. Hierarchical models were popular in classical blackboard systems but are here applied in a Bayesian setting as a mapping algorithm. The hierarchical models require reports of whisker distance to contact and of surface orientation at contact, and we demonstrate that this information can be retrieved by classifiers from strain data collected by CrunchBot's physical whiskers. We then provide a demonstration in simulation of how this information can be used to build maps (but not yet full SLAM) in an zero-odometry-noise environment containing walls and table-like hierarchical objects.

[1]  Hugh F. Durrant-Whyte,et al.  Simultaneous Localization, Mapping and Moving Object Tracking , 2007, Int. J. Robotics Res..

[2]  Paulo Cesar G. da Costa,et al.  Of Starships and Klingons: Bayesian Logic for the 23rd Century , 2005, UAI.

[3]  P. Green.  Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .

[4]  Tony J. Prescott,et al.  Hippocampus as unitary coherent particle filter , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[5]  Ehl Emile Aarts,et al.  Simulated annealing and Boltzmann machines , 2003 .

[6]  Charles W. Fox,et al.  ThomCat: A Bayesian Blackboard Model of Hierarchical Temporal Perception , 2008, FLAIRS.

[7]  Nathan F. Lepora,et al.  CrunchBot: A Mobile Whiskered Robot Platform , 2011, TAROS.

[8]  Michael A. Peshkin,et al.  Multifunctional Whisker Arrays for Distance Detection, Terrain Mapping, and Object Feature Extraction , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[9]  S. Sisson,et al.  Reversible jump Markov chain Monte Carlo , 2010, 1001.2055.

[10]  Jingjing Du,et al.  An application of Kullback-Leibler divergence to active SLAM and exploration with Particle Filters , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Mathew H. Evans,et al.  Tactile SLAM with a biomimetic whiskered robot , 2012, 2012 IEEE International Conference on Robotics and Automation.

[12]  W. Welker.  Analysis of Sniffing of the Albino Rat 1) , 1964 .

[13]  Dieter Fox,et al.  Adapting the Sample Size in Particle Filters Through KLD-Sampling , 2003, Int. J. Robotics Res..

[14]  Anthony G. Pipe,et al.  Whisking with robots , 2009, IEEE Robotics & Automation Magazine.

[15]  Geoffrey A. Hollinger,et al.  HERB: a home exploring robotic butler , 2010, Auton. Robots.

[16]  Luo Juan,et al.  A comparison of SIFT, PCA-SIFT and SURF , 2009 .

[17]  Anthony G. Pipe,et al.  From Rat Vibrissae to Biomimetic Technology for Active Touch , 2009 .

[18]  Nathan F. Lepora,et al.  Whisker-object contact speed affects radial distance estimation , 2010, 2010 IEEE International Conference on Robotics and Biomimetics.

[19]  D. Kleinfeld,et al.  'Where' and 'what' in the whisker sensorimotor system , 2008, Nature Reviews Neuroscience.

[20]  Patrick Henry Winston,et al.  Learning structural descriptions from examples , 1970 .

[21]  A. Ahl.  The role of vibrissae in behavior: A status review , 1986, Veterinary Research Communications.

[22]  D. Simons,et al.  Biometric analyses of vibrissal tactile discrimination in the rat , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[23]  Jason Wolfe,et al.  Sparse temporal coding of elementary tactile features during active whisker sensation , 2009, Nature Neuroscience.

[24]  Tony J. Prescott,et al.  Mapping with Sparse Local Sensors and Strong Hierarchical Priors , 2011, TAROS.

[25]  Oussama Khatib,et al.  Bayesian estimation for autonomous object manipulation based on tactile sensors , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[26]  Christoph Kayser,et al.  Texture signals in whisker vibrations. , 2006, Journal of neurophysiology.

[27]  Mathew H. Evans,et al.  Tactile Discrimination Using Template Classifiers: Towards a Model of Feature Extraction in Mammalian Vibrissal Systems , 2010, SAB.

[28]  S. Govindarajulu,et al.  A Comparison of SIFT, PCA-SIFT and SURF , 2012 .

[29]  A. Ng,et al.  Touch Based Perception for Object Manipulation , 2007 .

[30]  S. Panzeri,et al.  Diverse and Temporally Precise Kinetic Feature Selectivity in the VPm Thalamic Nucleus , 2008, Neuron.

[31]  R. Kruse,et al.  Guided Incremental Construction of Belief Networks , 2003 .

[32]  Wesley H. Huang,et al.  SLAM with sparse sensing , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[33]  R. Sinclair,et al.  Effects on discrimination performance of selective attention to tactile features. , 2000, Somatosensory & motor research.

[34]  Illtyd Trethowan.  Causality , 1938 .

[35]  Victor R. Lesser,et al.  The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty , 1980, CSUR.

[36]  Sharon A. Stansfield,et al.  Primitives, features, and exploratory procedures: Building a robot tactile perception system , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[37]  Wolfram Burgard,et al.  Information Gain-based Exploration Using Rao-Blackwellized Particle Filters , 2005, Robotics: Science and Systems.

[38]  Nir Friedman,et al.  Probabilistic Graphical Models - Principles and Techniques , 2009 .

[39]  Miriam Fend,et al.  Whisker-Based Texture Discrimination on a Mobile Robot , 2005, ECAL.

[40]  DaeEun Kim,et al.  Biomimetic whiskers for shape recognition , 2007, Robotics Auton. Syst..

[41]  Toshio Tsuji,et al.  Active antenna for contact sensing , 1998, IEEE Trans. Robotics Autom..

[42]  Siddhartha S. Srinivasa,et al.  GATMO: A Generalized Approach to Tracking Movable Objects , 2009, 2009 IEEE International Conference on Robotics and Automation.

[43]  Zeyn A. Saigol,et al.  Automated planning for hydrothermal vent prospecting using AUVs , 2011 .

[44]  Mitra J Z Hartmann,et al.  Using hardware models to quantify sensory data acquisition across the rat vibrissal array , 2007, Bioinspiration & biomimetics.

[45]  Anthony G. Pipe,et al.  Contact type dependency of texture classification in a whiskered mobile robot , 2009, Auton. Robots.

[46]  Nathan F. Lepora,et al.  Naive Bayes texture classification applied to whisker data from a moving robot , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[47]  Melanie Mitchell,et al.  Analogy-making as perception - a computer model , 1993, Neural network modeling and connectionism.

[48]  William Whittaker,et al.  Conditional particle filters for simultaneous mobile robot localization and people-tracking , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[49]  Jeffrey L. Krichmar,et al.  Texture discrimination by an autonomous mobile brain-based device with whiskers , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[50]  Emile H. L. Aarts,et al.  Simulated annealing and Boltzmann machines - a stochastic approach to combinatorial optimization and neural computing , 1990, Wiley-Interscience series in discrete mathematics and optimization.

[51]  Stuart J. Russell,et al.  Probabilistic models with unknown objects , 2006 .

[52]  Ben Mitchinson,et al.  Feedback control in active sensing: rat exploratory whisking is modulated by environmental contact , 2007, Proceedings of the Royal Society B: Biological Sciences.

[53]  Ying Zhang,et al.  Real-time indoor mapping for mobile robots with limited sensing , 2010, The 7th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2010).

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

[55]  Tod S. Levitt,et al.  Evidential Reasoning for Object Recognition , 2003, IEEE Trans. Pattern Anal. Mach. Intell..