Resource sharing for cloud robots: Service reuse and collective map building

Cloud robotics is proposed to describe a new approach that takes advantage of “internet as a resource” for real-time sharing of various resources and massively parallel computation. This study is to investigate how different kinds of internet resources can be located on the Internet for sharing among robots. It focuses on the sharing of robot services created by different developers and the building of a more complete environment map from the partial maps constructed by different robots. To verify our work, we perform a set of experiments and the results show the promise of the presented approach.

[1]  Ammad Ali,et al.  Face Recognition with Local Binary Patterns , 2012 .

[2]  Tsung-Hsien Yang,et al.  Configuring reusable robot services in a cloud environment , 2015, 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[3]  Pieter Abbeel,et al.  Image Object Label 3 D CAD Model Candidate Grasps Google Object Recognition Engine Google Cloud Storage Select Feasible Grasp with Highest Success Probability Pose EstimationCamera Robots Cloud 3 D Sensor , 2014 .

[4]  Stefano Carpin.  Merging maps via Hough transform , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Xiaojun Wu,et al.  DAvinCi: A cloud computing framework for service robots , 2010, 2010 IEEE International Conference on Robotics and Automation.

[6]  James A. Hendler,et al.  HTN planning for Web Service composition using SHOP2 , 2004, J. Web Semant..

[7]  Moritz Tenorth,et al.  The RoboEarth language: Representing and exchanging knowledge about actions, objects, and environments , 2012, 2012 IEEE International Conference on Robotics and Automation.

[8]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[9]  Wolfram Burgard,et al.  Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters , 2007, IEEE Transactions on Robotics.

[10]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[11]  Raffaello D'Andrea,et al.  Rapyuta: The RoboEarth Cloud Engine , 2013, 2013 IEEE International Conference on Robotics and Automation.

[12]  Wei-Po Lee,et al.  Enabling vision-based services with a cloud robotic system , 2016, 2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS).

[13]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[14]  Andreas Birk,et al.  Merging Occupancy Grid Maps From Multiple Robots , 2006, Proceedings of the IEEE.

[15]  M. Brian Blake,et al.  Distributed Service-Oriented Robotics , 2011, IEEE Internet Computing.

[16]  Guoqiang Hu,et al.  Cloud robotics: architecture, challenges and applications , 2012, IEEE Network.