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Satoshi Ueki

dblp:95/453 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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
3D vision · 77% Robot manipulation · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
depth image analysis
0.612022
Depth Distribution Split Labeling for Rubble Recognition of Crushing Machine · ICRA 2022

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

hydraulic cylinder pressure sensing · 0.6depth distribution split labeling · 0.6
YearPublicationVenuePosition
2022 Depth Distribution Split Labeling for Rubble Recognition of Crushing Machine
abstract
This paper describes rubble recognition using a depth image sensor and an automatic rubble crushing system using a construction machine for automatic rubble crushing at a building demolition site. Depth Distribution Split Labeling (DDSL) is proposed to recognize irregularly shaped rubble using depth images and to identify the largest rubble in the workspace. In DDSL, we focused on the fact that the depth of the contact area of adjacent rubble is lower, and labeling by dividing the depth makes it possible to identify the rubble. The automatic rubble crushing system enables to avoid excessive pushing and to grasp objects based on the cylinder driving force calculated from the hydraulic cylinder internal pressure of the construction machine. Through evaluation experiments simulating the crushing environment, it was confirmed that the proposed system can identify and automatically crush rubble.
Takahiro Ikeda, Satoshi Ueki, Kazuma Shinkai, Hironao Yamada
ICRA2