Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Hidekazu Niu

dblp:126/2713 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none

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 · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › deformable object manipulation
flexible material handling
0.011997
Performance improvement of flexible material handling robot by error detection and replanning · ICRA 1997
Robotics › Robot manipulation › deformable object manipulation
flexible payload handling
0.011997
Performance improvement of flexible material handling robot by error detection and replanning · ICRA 1997

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

replanning · 0.0error detection · 0.0control parameter adaptation · 0.0
YearPublicationVenuePosition
1997 Performance improvement of flexible material handling robot by error detection and replanning
abstract
This paper proposes a control system for the flexible material handling robot. In the past, there has been reported much research work on flexible material handling robot systems. In most of the previous work, control system parameters were treated as fixed. However, they often change due to variation of the flexible payloads. In some cases, control performance is degraded and the production process is terminated in some situations. To deal with these cases, we propose an error detection method and a replanning system. If system parameters change and control performance is degraded, this system detects error by itself and changes control parameters to recover from the error automatically. Some experimental examples are shown to confirm effectiveness of this proposed system.
Fumihito Arai, Hidekazu Niu, Toshio Fukuda
ICRA2