Cloud-assisted humanoid robotics for affective interaction

In recent years, the humanoid robot is received great attention, and gradually develop to households and personal service field. The prominent progress of cloud computing, big data, and machine learning fields provides a strong support for the research of the robot. With affective interaction ability of robot has a broad market space and research value. In this paper, we propose a cloud-assisted humanoid robotics for affective interaction system architecture, and introduce the essential composition, design and implementation of related components. Finally, through an actual robot emotional interaction test platform, validating the feasibility and extendibility of proposed architecture.

[1]  Ali Meghdari,et al.  Clinical Application of a Humanoid Robot in Pediatric Cancer Interventions , 2016, Int. J. Soc. Robotics.

[2]  Kerstin Dautenhahn,et al.  Using a Humanoid Robot to Elicit Body Awareness and Appropriate Physical Interaction in Children with Autism , 2015, Int. J. Soc. Robotics.

[3]  Min Chen,et al.  AIWAC: affective interaction through wearable computing and cloud technology , 2015, IEEE Wireless Communications.

[4]  Adriana Tapus,et al.  Haptic Human-Robot Affective Interaction in a Handshaking Social Protocol , 2015, 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[5]  Wafa Johal,et al.  A Cognitive and Affective Architecture for Social Human-Robot Interaction , 2015, HRI.

[6]  Michail G. Lagoudakis,et al.  Complete Analytical Forward and Inverse Kinematics for the NAO Humanoid Robot , 2015, J. Intell. Robotic Syst..

[7]  Ren-Hung Hwang,et al.  A buffer-aware HTTP live streaming approach for SDN-enabled 5G wireless networks , 2015, IEEE Network.

[8]  Zhang Zhen-mei,et al.  A Construction Strategy for Cloud Robotic System , 2014 .

[9]  Benjamin Robert Kehoe,et al.  Cloud-based Methods and Architectures for Robot Grasping , 2014 .

[10]  Paul Lukowicz,et al.  Towards Coexistence of Human and Robot: How Ubiquitous Computing Can Contribute? , 2014, RiTA.

[11]  Erik Blasch,et al.  A Holistic Cloud-Enabled Robotics System for Real-Time Video Tracking Application , 2014 .

[12]  Jiafu Wan,et al.  Cloud-assisted real-time transrating for http live streaming , 2013, IEEE Wireless Communications.

[13]  Mohsen Guizani,et al.  Exploring blind online scheduling for mobile cloud multimedia services , 2013, IEEE Wireless Communications.

[14]  Honggang Wang,et al.  A Network and Device Aware QoS Approach for Cloud-Based Mobile Streaming , 2013, IEEE Transactions on Multimedia.

[15]  Haohong Wang,et al.  Toward Blind Scheduling in Mobile Media Cloud: Fairness, Simplicity, and Asymptotic Optimality , 2013, IEEE Transactions on Multimedia.

[16]  Robert O. Ambrose,et al.  Robonaut 2 - The first humanoid robot in space , 2011, 2011 IEEE International Conference on Robotics and Automation.

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

[18]  Pierre Blazevic,et al.  Mechatronic design of NAO humanoid , 2009, 2009 IEEE International Conference on Robotics and Automation.

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

[20]  Martin Buss,et al.  Human-Robot Collaboration: a Survey , 2008, Int. J. Humanoid Robotics.