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Daniel W. Johnson

dblp:139/5344 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 1988
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

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
3 papers
Motion planning and robot control · 74% Robot navigation and mapping · 26%
Computer graphics and multimedia
2 papers
Geometric modeling and processing · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
collision detection
0.021988
A fast procedure for computing the distance between complex objects in three-dimensional space · IEEE J. Robotics Autom. 1988
A fast procedure for computing the distance between complex objects in three space · ICRA 1987
Geometric modeling and processing › computational geometry
distance computation between convex objects
0.011988
A fast procedure for computing the distance between complex objects in three-dimensional space · IEEE J. Robotics Autom. 1988
Geometric modeling and processing › collision detection
distance computation
0.011987
A fast procedure for computing the distance between complex objects in three space · ICRA 1987
Robotics › Robot navigation and mapping
obstacle avoidance
0.011985
Distance functions and their application to robot path planning in the presence of obstacles · IEEE J. Robotics Autom. 1985
Robotics › Motion planning and robot control
path planning
0.011985
Distance functions and their application to robot path planning in the presence of obstacles · IEEE J. Robotics Autom. 1985

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

convex set distance algorithm · 0.0gilbert-johnson-keerthi algorithm · 0.0convex optimization · 0.0optimal control · 0.0distance function · 0.0
YearPublicationVenuePosition
1988 A fast procedure for computing the distance between complex objects in three-dimensional space
abstract
An algorithm for computing the Euclidean distance between a pair of convex sets in R/sup m/ is described. Extensive numerical experience with a broad family of polytopes in R/sup 3/ shows that the computational cost is approximately linear in the total number of vertices specifying the two polytopes. The algorithm has special features which makes its application in a variety of robotics problems attractive. These features are discussed and an example of collision detection is given.>
Elmer G. Gilbert, Daniel W. Johnson, S. Sathiya Keerthi
IEEE J. Robotics Autom.2
1987 A fast procedure for computing the distance between complex objects in three space
abstract
An efficient and reliable algorithm for computing the Euclidean distance between a pair of convex sets in Rmdescribed. Extensive numerical experience with a broad family of polytopes in Rsshows that the computational cost is approximately linear in the total number of vertices specifying the two polytopes. The algorithm has special features which make its application in a variety of robotics problems attractive. These are discussed and an example of collision detection is given.
Elmer G. Gilbert, Daniel W. Johnson, S. Sathiya Keerthi
ICRA2
1985 Distance functions and their application to robot path planning in the presence of obstacles
abstract
An approach to robotic path planning, which allows optimization of useful performance indices in the presence of obstacles, is given. The main idea is to express obstacle avoidance in terms of the distances between potentially colliding parts. Mathematical properties of the distance functions are studied and it is seen that various types of derivatives of the distance functions are easily characterized. The results lead to the formulation of path planning problems as problems in optimal control and suggest numerical procedures for their solution. A simple numerical example involving a three-degree-of-freedom Cartesian manipulator is described.
Elmer G. Gilbert, Daniel W. Johnson
IEEE J. Robotics Autom.2