remote handling
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2021 ◽  
Vol 173 ◽  
pp. 112875
Author(s):  
Chang-Hwan Choi ◽  
Shanshuang Shi ◽  
Taku Yokoyama ◽  
Christopher Hall ◽  
Keelan Keogh ◽  
...  

2021 ◽  
Vol 172 ◽  
pp. 112794
Author(s):  
Pierre-Robert Pelletier ◽  
Frédéric Fuzier ◽  
Chang-Hwan Choi ◽  
Marco Van Uffelen ◽  
Mikel Bilbao Gutierrez ◽  
...  
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2021 ◽  
Vol 167 ◽  
pp. 112351
Author(s):  
Shijun Qin ◽  
Qingfeng Wang ◽  
Xiaoju Liu ◽  
Xianfeng Chen ◽  
Xuebing Peng ◽  
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2021 ◽  
Vol 165 ◽  
pp. 112216
Author(s):  
Sofía Coloma ◽  
Manuel Ferre ◽  
Fernando Arranz ◽  
Gioacchino Miccichè ◽  
Daniel Sánchez-Herranz ◽  
...  
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2021 ◽  
Vol 165 ◽  
pp. 112243
Author(s):  
Janne Lyytinen ◽  
Petri Tikka ◽  
Timo Määttä ◽  
Timo Avikainen ◽  
Seppo Rantala

Author(s):  
Hironari Obayashi ◽  
Hidemitsu Yoshimoto ◽  
Satoshi Kita ◽  
Kenichi Yamaki ◽  
Tao Wan ◽  
...  

2021 ◽  
Vol 164 ◽  
pp. 112048
Author(s):  
Yuto Noguchi ◽  
Kentaro Nakata ◽  
Nobukazu Takeda
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2021 ◽  
pp. 14-23
Author(s):  
Salvador Pacheco-Gutierrez ◽  
◽  
Ipek Caliskanelli ◽  
Robert Skilton

Remote handling systems are commonly used for decommissioning and maintenance of hazardous environments, especially in the nuclear sector. The necessity for a more realistic and accurate user interaction with the remote environment has led research towards the usage of immersive technologies such as augmented and virtual reality. In order for this to succeed, the state of the remote environment needs to be known accurately at all times. Information gathered using RGB-D cameras can serve this purpose. The high accuracy and density of data retrieved by these devices provide an extraordinary insight of the remote environment but can represent a burden on the communication channels. This paper addresses two point cloud compression techniques based on kd-trees and octrees for point cloud data transmission within a Robot Operative System (ROS) communications middleware.


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