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Denis E. Malone

dblp:73/807 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1994
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 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
1 paper
Motion planning and robot control · 44% Knowledge representation and reasoning · 44% Legged, aerial and field robots · 13%

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

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning › knowledge-based systems
knowledge-based control
0.011994
Knowledge Based Control in the Processing of Highly Varying Products · ICRA 1994
Robotics › Motion planning and robot control
robot control
0.011994
Knowledge Based Control in the Processing of Highly Varying Products · ICRA 1994
Robotics › Legged, aerial and field robots
field robotics
0.011994
Knowledge Based Control in the Processing of Highly Varying Products · ICRA 1994

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

sensing · 0.0a priori knowledge · 0.0
YearPublicationVenuePosition
1994 Knowledge Based Control in the Processing of Highly Varying Products
abstract
Natural products, such as food products derived from animals and plants, exhibit a high degree of variability. Key factors for successful automation of these processes are the ability to sense workpiece variations and the flexibility to alter control strategies accordingly. This paper describes a robot system which incorporates complex sensing with knowledge based control. The system is used to remove the lateral pin bones from fish fillets by means of a robot manipulated waterjet cutter. A sensing system is used to obtain geometric and positional information about each fillet. A knowledge based control system uses a priori knowledge of the fish species and information from the sensing system to generate the appropriate robot commands. The successful deboning of fish fillets demonstrates the viability of this approach.>
Denis E. Malone, Werner E. Friedrich, Natalie R. Spooner, Patrick P. K. Lim
ICRA1