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Yoshimasa Sato

dblp:44/6981 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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
2 papers
Robot manipulation · 59% Motion planning and robot control · 41%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.011995
Development of Multi-Arm Robots for Automobile Assembly · ICRA 1995
Robotics › Motion planning and robot control › robot control › torque control
joint torque control
0.011995
Development of a Fast Assembly Robot Arm with Joint Torque Sensory Feedback Control · ICRA 1995
Robotics › Robot manipulation › cooperative manipulation
multi-arm assembly
0.011995
Development of Multi-Arm Robots for Automobile Assembly · ICRA 1995
Robotics › Motion planning and robot control
robot control
0.011995
Development of a Fast Assembly Robot Arm with Joint Torque Sensory Feedback Control · ICRA 1995
Robotics › Robot manipulation
robot design
0.011995
Development of a Fast Assembly Robot Arm with Joint Torque Sensory Feedback Control · ICRA 1995
Robotics › Motion planning and robot control › robot control
compliant motion control
0.011995
Development of a Fast Assembly Robot Arm with Joint Torque Sensory Feedback Control · ICRA 1995
Robotics › Robot manipulation
dexterous manipulation
0.011995
Development of Multi-Arm Robots for Automobile Assembly · ICRA 1995

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

torque sensory feedback · 0.0nonlinear torque compensation · 0.0inertial torque feedforward compensation · 0.0
YearPublicationVenuePosition
1995 Development of a Fast Assembly Robot Arm with Joint Torque Sensory Feedback Control
abstract
We have developed a new robot arm with six joints that have torque sensors and geared reduction systems. This arm has compliance control ability without using a wrist force sensor. The techniques adopted here are the low friction and low gear ratio reduction system, nonlinear torque compensation, inertial torque feedforward compensation and joint torque control using joint torque sensor feedback. The experimental results show that this robot has high accuracy of trajectory in spite of large compliance, i.e. low position feedback gains. This robot can also take practical industrial tasks in high speed under uncertain positioning of works.
Yuji Tsusaka, Mitsuo Koide, Minoru Tanaka, Hideki Nomura, Toshitaka Kuno, Shigetaka Nagamatsu, Norihiko Akao, Yoshimasa Sato, Tadashi Naito
ICRA8
1995 Development of Multi-Arm Robots for Automobile Assembly
abstract
Numerous issues remain to be solved in improving the efficiency of the complex assembly processes existing in the automobile chassis and drive train system assembling plants due to their being labor intensive and their reliance on the dexterity of human operators. Equally important, factors such as labor shortages and reduced work hours are expected to become more of an issue in the coming years. It is extremely important, therefore, to address the qualitative and quantitative issues of labor in the design and manufacturing aspects of the assembly line, as well as the issue of the assembly operators themselves. To address these issues, we have developed and put into practical use a multi-arm type assembly robot capable of handling complex and both-hands assembly operations. In this paper, we present its development concept, performance, and examples of actual applications.
Shigetaka Nagamatsu, Yoshimasa Sato
ICRA3