Robot control system for safe and rapid programming of grinding applications

Thomessen, Trygve; Lien, Terje K.

doi:10.1108/01439910010355766

Cited by 19 publications

(14 citation statements)

References 2 publications

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“…Since not all companies employ robotic experts these modifications prove problematic for some, especially in case of complex applications like grinding or deburring (Thomessen (2000)), when working in direct contact with the work piece and where workpiece geometry is often complex. This raises a demand for robotic experts that assist users with modifications of their programs or can provide support in case of errors or undesirable results.…”

Section: Introductionmentioning

confidence: 99%

Augmented Reality for Telemaintenance and -inspection in Force-Sensitive Industrial Robot Applications

Leutert

Schilling

2015

IFAC-PapersOnLine

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Telematic solutions allow fast remote support in industrial robot work cells: Robotic experts can assist the local staff in work process modifications or in tracking down errors without having to actually travel to the remote site. In order to be able to perform such teleinspection and telemaintenance tasks the operator needs to establish a data connection to the robot and get an understanding of the remote work process, as well as of the transmitted data.This contribution introduces a telematic control system developed for remote monitoring and control of an industrial robot performing force-sensitive work applications. An Augmented Reality interface is proposed for intuitive representation of complex robotic data, allowing quick analysis of the current working cycle and process data and altering the robot's program remotely while still having a clear spatial reference to the work environment.

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Section: Introductionmentioning

confidence: 99%

Augmented Reality for Telemaintenance and -inspection in Force-Sensitive Industrial Robot Applications

Leutert

Schilling

2015

IFAC-PapersOnLine

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“…At least older robot controllers do not support such possibility of sensor fusion within the control architecture. Several academic researches have been focusing in this field where some choose to entirely replace the original controller like Garcia et al (2004) while others again include their own subsystem in-between the control loop, like Blomdell et al (2005) and Thomessen & Lien (2000). To address problems related to sensor integration in robotic applications several general architectures, named middleware's, are being developed for easy system integration.…”

mentioning

confidence: 99%

“…Kalpakjian & Scmid (2006) states that a manual de-burring operation can add up to 10% on the manufacturing cost. In general manual grinding, de-burring and polishing are heavy and in many cases unhealthy work-tasks where the workers need to wear protective equipment such as goggles, gloves and earmuffs (Thomessen et al, 1999).…”

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confidence: 99%

Robot Programming in Machining Operations

Solvang¹,

Sziebig²,

Köröndi³

2008

Robot Manipulators

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Driven by the need for higher -flexibility and -speed during initial programming and path adjustments, new robot programming methodologies quickly arises. The traditional "Teach" and "Offline" programming methodologies have distinct weaknesses in machining applications. "Teach" programming is time consuming when used on freeform surfaces or in areas with limited visibility /accessibility. Also, "Teach" programming only relates to the real work-piece and there is no connection to the ideal CAD model of the work-piece. Vice versa during offline programming there is no knowledge about the real work-piece, only the ideal CAD model is used. To be able to relate to both the real-and ideal-model of the work-piece is especially important in machining operations where the difference between the models often represents the necessary material removal . In this chapter an introduction to a programming methodology especially targeted for machining applications is given. This methodology use a single camera combined with image processing algorithms like edge-and colour-detection, combines information of the real and ideal work-piece and represents a human friendly and effective approach for robot programming in machining operations.

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“…Contour tracking is, on the contrary, an example of a complex task that requires the manipulator to continuously and autonomously modify its path, coping with the uncertainties typical of unstructured environments (Siciliano & Villani, 1999). In many applications a robot is required to follow a contour while applying a normal force; these tasks include grinding (Thomessen & Lien, 2000), deburring (Ferretti et al, 2000;Ziliani et al, 2005), shape recovery (Ahmad & Lee, 1990), polishing and kinematic calibration (Legnani et al, 2001). The problem of tracking (known and) unknown contours has been studied by many researchers in the last two decades.…”

Section: Introductionmentioning

confidence: 99%