Active In-Hand Object Recognition on a Humanoid Robot

For any robot, the ability to recognize and manipulate unknown objects is crucial to successfully work in natural environments. Object recognition and categorization is a very challenging problem, as 3-D objects often give rise to ambiguous, 2-D views. Here, we present a perception-driven exploration and recognition scheme for in-hand object recognition implemented on the iCub humanoid robot. In this setup, the robot actively seeks out object views to optimize the exploration sequence. This is achieved by regarding the object recognition problem as a localization problem. We search for the most likely viewpoint position on the viewsphere of all objects. This problem can be solved efficiently using a particle filter that fuses visual cues with associated motor actions. Based on the state of the filter, we can predict the next best viewpoint after each recognition step by searching for the action that leads to the highest expected information gain. We conduct extensive evaluations of the proposed system in simulation as well as on the actual robot and show the benefit of perception-driven exploration over passive, vision-only processes at discriminating between highly similar objects. We demonstrate that objects are recognized faster and at the same time with a higher accuracy.

[1]  Olivier Stasse,et al.  Online object search with a humanoid robot , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Angelo Cangelosi,et al.  The iCub Humanoid Robot Simulator , 2008 .

[3]  Nicholas J. Butko,et al.  Active perception , 2010 .

[4]  Olivier Stasse,et al.  A next-best-view algorithm for autonomous 3D object modeling by a humanoid robot , 2008, Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots.

[5]  Heinrich H. Bülthoff,et al.  Object Recognition in Humans and Machines , 2007 .

[6]  Dana H. Ballard,et al.  Animate Vision , 1991, Artif. Intell..

[7]  Shengyong Chen,et al.  Active vision in robotic systems: A survey of recent developments , 2011, Int. J. Robotics Res..

[8]  John K. Tsotsos,et al.  Active object recognition , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Tamim Asfour,et al.  Autonomous acquisition of visual multi-view object representations for object recognition on a humanoid robot , 2010, 2010 IEEE International Conference on Robotics and Automation.

[10]  Hiroshi Murase,et al.  Visual learning and recognition of 3-d objects from appearance , 2005, International Journal of Computer Vision.

[11]  Ales Ude,et al.  Sensorimotor processes for learning object representations , 2007, 2007 7th IEEE-RAS International Conference on Humanoid Robots.

[12]  Wolfram Burgard,et al.  Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .

[13]  Yiannis Aloimonos,et al.  Active vision , 2004, International Journal of Computer Vision.

[14]  Mongi A. Abidi,et al.  Best-next-view algorithm for three-dimensional scene reconstruction using range images , 1995, Other Conferences.

[15]  David S. Wettergreen,et al.  Active localization on the ocean floor with multibeam sonar , 2008, OCEANS 2008.

[16]  N. Gordon,et al.  Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .

[17]  Giorgio Metta,et al.  Active object recognition on a humanoid robot , 2012, 2012 IEEE International Conference on Robotics and Automation.

[18]  Dieter Fox,et al.  Autonomous generation of complete 3D object models using next best view manipulation planning , 2011, 2011 IEEE International Conference on Robotics and Automation.

[19]  Irving Biederman,et al.  Object recognition, attention, and action , 2007 .

[20]  Tamim Asfour,et al.  Active multi-view object search on a humanoid head , 2009, 2009 IEEE International Conference on Robotics and Automation.

[21]  Heiko Wersing,et al.  Active 3D Object Localization Using a Humanoid Robot , 2011, IEEE Transactions on Robotics.

[22]  Subhashis Banerjee,et al.  Active recognition through next view planning: a survey , 2004, Pattern Recognit..

[23]  Lucas Paletta,et al.  Active object recognition by view integration and reinforcement learning , 2000, Robotics Auton. Syst..

[24]  John K. Tsotsos,et al.  50 Years of object recognition: Directions forward , 2013, Comput. Vis. Image Underst..

[25]  Joachim Denzler,et al.  Information Theoretic Sensor Data Selection for Active Object Recognition and State Estimation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Frank P. Ferrie,et al.  Active Object Recognition: Looking for Differences , 2001, International Journal of Computer Vision.

[27]  Sven J. Dickinson,et al.  Active Object Recognition Integrating Attention and Viewpoint Control , 1997, Comput. Vis. Image Underst..

[28]  Tamim Asfour,et al.  Object separation using active methods and multi-view representations , 2008, 2008 IEEE International Conference on Robotics and Automation.