<title>Algorithmic approach to system state monitoring via multiple-sensor integration</title>

Hybrid assembly cells allow humans and robots to collaborate on assembly tasks. We consider a model of the hybrid cell in which a human and a robot asynchronously collaborate to assemble a product. The human retrieves parts from a bin and places them in the robot’s workspace, while the robot picks up the placed parts and assembles them into the product. Realizing hybrid cells requires -automated plan generation, system state monitoring, and contingency handling. In this paper we describe system state monitoring and present a characterization of the part matching algorithm. Finally, we report results from human-robot collaboration experiments using a KUKA robot and a 3D-printed mockup of a simplified jet-engine assembly to illustrate our approach.

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Multiple sensor integration for indoor surveillance

Proceedings of the 6th international workshop on Multimedia data mining mining integrated media and complex data - MDM '05 ◽

10.1145/1133890.1133896 ◽

2005 ◽

Author(s):

Valery A. Petrushin ◽

Gang Wei ◽

Rayid Ghani ◽

Anatole V. Gershman

Keyword(s):

Sensor Integration ◽

Multiple Sensor

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Design of Hybrid Cells to Facilitate Safe and Efficient Human–Robot Collaboration During Assembly Operations

Journal of Computing and Information Science in Engineering ◽

10.1115/1.4039061 ◽

2018 ◽

Vol 18 (3) ◽

Cited By ~ 1

Author(s):

Krishnanand N. Kaipa ◽

Carlos W. Morato ◽

Satyandra K. Gupta

Keyword(s):

Three Dimensional ◽

System State ◽

Hybrid Cells ◽

Generation System ◽

State Monitoring ◽

Plan Generation ◽

3D Printed ◽

Assembly Operations ◽

Human Robot Collaboration

This paper presents a framework to build hybrid cells that support safe and efficient human–robot collaboration during assembly operations. Our approach allows asynchronous collaborations between human and robot. The human retrieves parts from a bin and places them in the robot's workspace, while the robot picks up the placed parts and assembles them into the product. We present the design details of the overall framework comprising three modules—plan generation, system state monitoring, and contingency handling. We describe system state monitoring and present a characterization of the part tracking algorithm. We report results from human–robot collaboration experiments using a KUKA robot and a three-dimensional (3D)-printed mockup of a simplified jet-engine assembly to illustrate our approach.

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Multiple sensor integration with the SonTek Hydra datalogger: IEEE sixth working conference on current measurement

Proceedings of the IEEE Sixth Working Conference on Current Measurement (Cat. No.99CH36331) ◽

10.1109/ccm.1999.755235 ◽

1999 ◽

Author(s):

J. Mullison ◽

R. Cabrera ◽

D. Slocum

Keyword(s):

Current Measurement ◽

Sensor Integration ◽

Multiple Sensor

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WILDFIRE DETECTION AND DISASTER MONITORING SYSTEM USING UAS AND SENSOR FUSION TECHNOLOGIES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b3-2020-1671-2020 ◽

2020 ◽

Vol XLIII-B3-2020 ◽

pp. 1671-1675

Author(s):

T. Kanand ◽

G. Kemper ◽

R. König ◽

H. Kemper

Keyword(s):

Sensor Fusion ◽

Mobile Network ◽

Automated Analysis ◽

Technological Advance ◽

Sensor Integration ◽

Data Infrastructure ◽

Advanced Technologies ◽

5G Network ◽

Disaster Monitoring ◽

Multiple Sensor

Abstract. Based on a research program founded by the German Ministry of Traffic and Data Infrastructure, the use of 5G mobile network for modern advanced technologies should be developed and tested. This paper shows the integration of UAS, Multiple Sensor Integration, autonomous UAS Missions and online Geodata handling for the detection of wildfires in a rural region of Saxony / East Germany and the strategy for making use of the upcoming 5G Network. In our project we go a step deeper and combine VIS and Thermal IR cameras in a co-registered way to overlay the images, transfer data of multi-observation poles into a center and perform an automated analysis to detect smoke or hotspots and add to a first estimated localization. The technological advance applied on real project areas means an important step for further applications of UAS and Sensor Fusion Technologies.

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