Human-Robot Interaction by Whole Body Gesture Spotting and Recognition

2006 ◽  
Author(s):  
Hee-Deok Yang ◽  
A-Yeon Park ◽  
Seong-Whan Lee
Keyword(s):  
Human Robot Interaction ◽  
Whole Body ◽  
Robot Interaction ◽  
Gesture Spotting

Gesture Spotting and Recognition for Human–Robot Interaction

2007 ◽  
Vol 23 (2) ◽  
pp. 256-270 ◽  
Author(s):  
Hee-Deok Yang ◽  
A-Yeon Park ◽  
Seong-Whan Lee
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction ◽  
Gesture Spotting

scholarly journals Multi-connection load compensation and load information calculation for an upper-limb exoskeleton based on a six-axis force/torque sensor

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986318 ◽  
Author(s):  
Xin Wang ◽  
Qiuzhi Song ◽  
Shitong Zhou ◽  
Jing Tang ◽  
Kezhong Chen ◽  
...  
Keyword(s):  
Upper Limb ◽  
Interaction Force ◽  
Center Of Gravity ◽  
Human Robot Interaction ◽  
Whole Body ◽  
Torque Sensor ◽  
Robot Interaction ◽  
End Effector ◽  
Load Compensation ◽  
Upper Limb Exoskeleton

In this article, a method of multi-connection load compensation and load information calculation for an upper-limb exoskeleton is proposed based on a six-axis force/torque sensor installed between the exoskeleton and the end effector. The proposed load compensation method uses a mounted sensor to measure the force and torque between the exoskeleton and load of different connections and adds a compensator to the controller to compensate the component caused by the load in the human–robot interaction force, so that the human–robot interaction force is only used to operate the exoskeleton. Therefore, the operator can manipulate the exoskeleton with the same interaction force to lift loads of different weights with a passive or fixed connection, and the human–robot interaction force is minimized. Moreover, the proposed load information calculation method can calculate the weight of the load and the position of its center of gravity relative to the exoskeleton and end effector accurately, which is necessary for acquiring the upper-limb exoskeleton center of gravity and stability control of whole-body exoskeleton. In order to verify the effectiveness of the proposed method, we performed load handling and operational stability experiments. The experimental results showed that the proposed method realized the expected function.

scholarly journals Robots that look like humans: A brief look into humanoid robotics

2018 ◽  
Author(s):  
Eiichi Yoshida
Keyword(s):  
Degrees Of Freedom ◽  
Large Scale ◽  
Humanoid Robots ◽  
Pattern Generation ◽  
Human Robot Interaction ◽  
Cognitive Robotics ◽  
Body Motion ◽  
Upper Body ◽  
Whole Body ◽  
Robot Interaction

This article provides a brief overview of the technology of humanoid robots. First, historical development and hardware progress are presented mainly on human-size full-body biped humanoid robots, together with progress in pattern generation of biped locomotion. Then, «whole-body motion» – coordinating leg and arm movements to fully leverage humanoids’ high degrees of freedom – is presented, followed by its applications in fields such as device evaluation and large-scale assembly. Upper-body humanoids with a mobile base, which are mainly utilized for research on human-robot interaction and cognitive robotics, are also introduced before addressing current issues and perspectives.

scholarly journals Detecting Human-Robot Interaction using Locality of Haptic Features through Skin Sensors Embedded on the Whole Body

2009 ◽  
Vol 27 (6) ◽  
pp. 669-678
Author(s):  
Tomoyuki Noda ◽  
Takahiro Miyashita ◽  
Hiroshi Ishiguro ◽  
Norihiro Hagita
Keyword(s):  
Human Robot Interaction ◽  
Whole Body ◽  
Robot Interaction

scholarly journals The CoDyCo Project Achievements and Beyond: Toward Human Aware Whole-Body Controllers for Physical Human Robot Interaction

2018 ◽  
Vol 3 (1) ◽  
pp. 516-523 ◽  
Author(s):  
Francesco Romano ◽  
Gabriele Nava ◽  
Morteza Azad ◽  
Jernej Camernik ◽  
Stefano Dafarra ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Whole Body ◽  
Robot Interaction

scholarly journals A Multilayer Hidden Markov Models-Based Method for Human-Robot Interaction

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Chongben Tao ◽  
Guodong Liu
Keyword(s):  
Hidden Markov Models ◽  
Gesture Recognition ◽  
Markov Models ◽  
Hidden Markov ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Threshold Criterion ◽  
Feed Forward Neural Networks ◽  
Recognition Errors ◽  
Gesture Spotting

To achieve Human-Robot Interaction (HRI) by using gestures, a continuous gesture recognition approach based on Multilayer Hidden Markov Models (MHMMs) is proposed, which consists of two parts. One part is gesture spotting and segment module, the other part is continuous gesture recognition module. Firstly, a Kinect sensor is used to capture 3D acceleration and 3D angular velocity data of hand gestures. And then, a Feed-forward Neural Networks (FNNs) and a threshold criterion are used for gesture spotting and segment, respectively. Afterwards, the segmented gesture signals are respectively preprocessed and vector symbolized by a sliding window and a K-means clustering method. Finally, symbolized data are sent into Lower Hidden Markov Models (LHMMs) to identify individual gestures, and then, a Bayesian filter with sequential constraints among gestures in Upper Hidden Markov Models (UHMMs) is used to correct recognition errors created in LHMMs. Five predefined gestures are used to interact with a Kinect mobile robot in experiments. The experimental results show that the proposed method not only has good effectiveness and accuracy, but also has favorable real-time performance.

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