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N. A. Duffie

dblp:21/5984 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1987
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 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
1 paper
Robot manipulation · 77% Robot navigation and mapping · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
mobile manipulation
0.011987
On-line compensation of mobile robot docking errors · IEEE J. Robotics Autom. 1987
Robotics › Robot navigation and mapping
vision-based sensing
0.011987
On-line compensation of mobile robot docking errors · IEEE J. Robotics Autom. 1987

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

vision-based error sensing · 0.0touch trigger probe · 0.0
YearPublicationVenuePosition
1987 On-line compensation of mobile robot docking errors
abstract
One of the main problems of an unconstrained mobile robot (that is not limited to rails or tracks), that limits its industrial applications, is its docking accuracy. Because robot programs are executed relative to the robot base, inaccurate positioning of the mobile robot during docking must be accounted for in order to improve the accuracy of the mobile robot. In this paper, a method to compensate for the docking inaccuracy of mobile robots is proposed. The method is based on modifying the task of the robot arm according to the docking error-the offset between the desired and actual docking locations of the mobile robot. The docking error is sensed by a sensor mounted on the robot arm: it can be either a vision system or a touch trigger probe. The algorithms for calculating the spatial docking error for each sensor and how the robot's task is modified accordingly are presented. The need for a method that will allow to reach results even in the presence of perturbed data, something that currently applied methods cannot guarantee, is discussed and one is presented. The calculation of the spatial offset between the actual and the desired locations of the mobile robot using vision system was implemented and results of some experiments are presented and discussed.
K. Mandel, N. A. Duffie
IEEE J. Robotics Autom.2