scholarly journals Guest Editorial: Integrating sensor fusion and perception for human–robot interaction

2021 ◽  
Vol 3 (3) ◽  
pp. 183-186
Author(s):  
Hang Su ◽  
Jing Guo ◽  
Wen Qi ◽  
Mingchuan Zhou ◽  
Yue Chen
Keyword(s):  
Sensor Fusion ◽  
Guest Editorial ◽  
Human Robot Interaction ◽  
Robot Interaction

Guest Editorial Special Issue on Human–Robot Interaction

2007 ◽  
Vol 23 (5) ◽  
pp. 837-839 ◽  
Author(s):  
Cecilia Laschi ◽  
Cynthia Breazeal ◽  
Yasushi Nakauchi
Keyword(s):  
Guest Editorial ◽  
Human Robot Interaction ◽  
Special Issue ◽  
Robot Interaction ◽  
Editorial Special Issue

scholarly journals An Augmented Reality Based Human-Robot Interaction Interface Using Kalman Filter Sensor Fusion

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4586 ◽  
Author(s):  
Chunxu Li ◽  
Ashraf Fahmy ◽  
Johann Sienz
Keyword(s):  
Kalman Filter ◽  
Augmented Reality ◽  
Sensor Fusion ◽  
Kalman Filtering ◽  
Control Process ◽  
Human Robot Interaction ◽  
Post Processing ◽  
Robot Interaction ◽  
Kinect Camera ◽  
Interaction Interface

In this paper, the application of Augmented Reality (AR) for the control and adjustment of robots has been developed, with the aim of making interaction and adjustment of robots easier and more accurate from a remote location. A LeapMotion sensor based controller has been investigated to track the movement of the operator hands. The data from the controller allows gestures and the position of the hand palm’s central point to be detected and tracked. A Kinect V2 camera is able to measure the corresponding motion velocities in x, y, z directions after our investigated post-processing algorithm is fulfilled. Unreal Engine 4 is used to create an AR environment for the user to monitor the control process immersively. Kalman filtering (KF) algorithm is employed to fuse the position signals from the LeapMotion sensor with the velocity signals from the Kinect camera sensor, respectively. The fused/optimal data are sent to teleoperate a Baxter robot in real-time by User Datagram Protocol (UDP). Several experiments have been conducted to test the validation of the proposed method.

Multi-sensor fusion for body sensor network in medical human–robot interaction scenario

2020 ◽  
Vol 57 ◽  
pp. 15-26 ◽  
Author(s):  
Kai Lin ◽  
Yihui Li ◽  
Jinchuan Sun ◽  
Dongsheng Zhou ◽  
Qiang Zhang
Keyword(s):  
Sensor Network ◽  
Sensor Fusion ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Body Sensor Network

A Comparison of Bystander and Team Member Distance in Human--Robot Interaction

2014 ◽  
Author(s):  
Mitchell S. Dunfee ◽  
Tracy Sanders ◽  
Peter A. Hancock
Keyword(s):  
Team Member ◽  
Human Robot Interaction ◽  
Robot Interaction
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