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Andrew E. Brennemann

dblp:71/2120 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 1995
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 3 first-authorSystems, architecture and hardware · 3 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Robot manipulation · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
assembly
0.021994
Accurate Alignment of Laminate Materials Using Sensor-Based Robot Techniques · ICRA 1994
Sensors for robotic assembly · ICRA 1988
Robotics › Robot manipulation › assembly
sensor-based assembly
0.021994
Sensors for robotic assembly · ICRA 1988
Accurate Alignment of Laminate Materials Using Sensor-Based Robot Techniques · ICRA 1994
Robotics › Robot manipulation
precision positioning
0.011988
Sensors for robotic assembly · ICRA 1988

Methods — techniques the papers use, named apart from their topics

optical sensing · 0.0tactile-vision sensing · 0.0machine vision · 0.0fiber-optic sensing · 0.0
YearPublicationVenuePosition
1995 Magnetic and optical-fluorescence position sensing for planar linear motors
abstract
Planar linear motors, e.g. Sawyer motors, operate in an open-loop stepping-manner. This mode of operation makes them: 1) susceptible to loss of steps, 2) unable to reject external disturbances, 3) unable to provide controlled forces, and 4) unable to provide high stiffness. These limitations, in turn, restrict their usefulness in a wide range of robotic applications. Suitable position sensing and control technology, when added to such motors, can to a large degree eliminate these problems. In this paper we present two new sensor technologies for planar motor systems: one uses an AC magnetic technique, the other uses an optical fluorescence technique. The magnetic sensor has achieved 1 /spl mu/m position resolution and is compact and easy to fabricate. The optical fluorescence sensor has the advantage of complete insensitivity to nearby motor fields. Either technology has the potential to greatly improve future robotic systems that are based on planar linear motors.
Andrew E. Brennemann, Ralph L. Hollis
IROS (3)1
1994 Accurate Alignment of Laminate Materials Using Sensor-Based Robot Techniques
abstract
Assembly accuracies of 0.05-0.1 mm, needed for electronic product manufacture, are attainable with current automated manufacturing equipment. Aggressive electronic system designs will require manufacturing accuracies in the range of 0.005-0.01 mm. A system and strategy is described here to fabricate circuit boards requiring alignment accuracies of 7.5 /spl mu/m using existing automation equipment with enhancements and typical manufacturing line fixtures. The system, configured as a pilot workcell, consisted of an IBM 7576 coarse positioning robot, a fine positioning manipulator, an optical sensing system and a unique bracing method to reduce environmental disturbances. The strategy was to use a coarse/fine placement technique with sensing to align, stack and bond individual test laminates with patterns of 100 /spl mu/m holes. The results showed that pairs of holes were consistently aligned to 2-5 /spl mu/m which surpasses the 7.5 /spl mu/m manufacturing requirement.>
Andrew E. Brennemann, Robert Hammer, Ralph L. Hollis, William V. Jecusco II
ICRA1
1988 Sensors for robotic assembly
abstract
Special-purpose sensors and hybrid mechanical systems have been developed to assemble advanced electronic circuits. State-of-the-art robot systems that are used for electronic assembly and accuracy requirements for the developing surface mount technology are reviewed, showing the need for improved robot positioning capability. Examples of laboratory experiments that demonstrated successful precision assembly or testing using an ordinary robot, a micropositioner, and an optical sensing system are given. These involve fiber-optic sensing, machine-vision endpoint sensing, and hybrid tactic-vision endpoint sensing.>
Andrew E. Brennemann, Ralph L. Hollis, Mark A. Lavin, Bela L. Musits
ICRA1