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Ouboti Djaneye-Boundjou

dblp:179/9705 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · unresolved

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

Artificial 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
1 paper
Robot manipulation · 33% Motion planning and robot control · 33% 3D vision · 33%
Theoretical computer science
1 paper
Mathematical optimization · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
industrial robot
0.312018
Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018
Robotics › Motion planning and robot control › robot calibration
kinematic calibration
0.312018
Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018
Computer vision › 3D vision › camera calibration
self-calibration
0.312018
Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018
Mathematical optimization
metaheuristic optimization
0.112018
Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018
Mathematical optimization › metaheuristic optimization › swarm intelligence
particle swarm optimization
0.112018
Geometry Based Self Kinematic Calibration Method for Industrial Robots · ICRA 2018

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

particle swarm optimization · 0.7geometric calibration · 0.7
YearPublicationVenuePosition
2018 Geometry Based Self Kinematic Calibration Method for Industrial Robots
abstract
Accuracy of robots is an important facet in an industrial setting. In this paper, we present a novel kinematic calibration methodology. Traditional calibration techniques require an external metrology device. Unlike those, the presented product here is highly practical in that it does not require a metrology device. The kinematic calibration model is formulated by making use of the robot itself as a metrology device to measure the geometry of a known artifact. The optimal parameters/characteristics of the model are identified using a Particle Swarm Optimization (PSO) technique. Our experimental results show that this new approach provides results comparable to those generated using spatial information provided by a Coordinate Measurement Machine (CMM). Using this new approach (GageCAL), the Yaskawa Motoman “MHS-Hi” robot is calibrated. Our experimental testing also indicates that this methodology can be extended to a wide variety of anthropomorphic robots.
Temesguen Messay, George Sutton, Ouboti Djaneye-Boundjou
ICRA3