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Tsuyoshi Nishiyama

dblp:77/4613 · DBLP profile ↗
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5ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none

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

Artificial intelligence and machine learning · 5Systems, architecture and hardware · 5

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
Motion planning and robot control · 41% 3D vision · 32% Robot manipulation · 27%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.012003
Design of an artificial mark to determine 3D pose by monocular vision · ICRA 2003
Computer vision › 3D vision › pose estimation
monocular pose estimation
0.012003
Design of an artificial mark to determine 3D pose by monocular vision · ICRA 2003
Robotics › Robot manipulation › grasping
object handling
0.012003
Design of an artificial mark to determine 3D pose by monocular vision · ICRA 2003
Robotics › Motion planning and robot control
path planning
0.012003
Smooth path planning by using visibility graph-like method · ICRA 2003
Computer vision › 3D vision
pose estimation
0.012003
Design of an artificial mark to determine 3D pose by monocular vision · ICRA 2003
Robotics › Motion planning and robot control › path planning
smooth path planning
0.012003
Smooth path planning by using visibility graph-like method · ICRA 2003
Robotics › Motion planning and robot control › path planning
visibility graph
0.012003
Smooth path planning by using visibility graph-like method · ICRA 2003

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

gravity center calculation · 0.0color extraction · 0.0clothoid arcs · 0.0bëzier curves · 0.0
YearPublicationVenuePosition
2003 Design of an artificial mark to determine 3D pose by monocular vision
abstract
The design for an artificial mark attached to small objects is presented in this paper. Three conditions are required for the design of the marks: (1) short calculation time, (2) easy attachment, and (3) individual calculation for each item. The marks are obtained by using three different extraction methods. The experiments determine the best mark. The mark using the method that extract colors and calculated the gravity has good results. We analyze the errors of the mark that has best experiment. The appropriateness of the experimental results is then confirmed. We have the experiment that the manipulator handles the objects with the best mark. The experiment is successful. Therefore, the usability of the mark is verified.
Rie Katsuki, Jun Ota 0001, Takahisa Mizuta, Tomomi Kito, Tamio Arai, Tsuyoshi Ueyama, Tsuyoshi Nishiyama
ICRA7
2003 Smooth path planning by using visibility graph-like method
abstract
To achieve smooth motion of car-like robots, it is necessary to generate paths that satisfy the following conditions: maximum curvature, maximum curvature derivative, and curvature continuity. Another requirement is that human operators can manipulate the robots with ease. In this paper, a path expression methodology consisting of line segments, circular arcs and clothoid arcs is presented. In addition, a method of global path generation with a visibility graph is proposed. To establish this method, the following steps are proposed: (a) the arrangement of subgoals (middle points) and (b) the construction of the graph for path generation. By using the proposed method, the paths were shortened 14% on average.
Tomomi Kito, Jun Ota 0001, Rie Katsuki, Takahisa Mizuta, Tamio Arai, Tsuyoshi Ueyama, Tsuyoshi Nishiyama
ICRA7
2003 Handling of objects with marks by a robot
abstract
This paper presents a robot system for handling various objects in home or office environments. A fixed manipulator utilizes marks on objects for handling and motion planning. A mark consists of two parts. One is the outer part, which indicates its pose (in this paper, "pose " denotes 3D position and orientation), and the other is a QR code, which is a kind of 2D barcode. A QR code is stored information of an object (e.g. its name). A user attaches several marks on each object. The manipulator accesses the information using a camera in its hand. The robot can decide its complex handling motion based on the information in QR codes, pose of the objects, which are estimated from pose of marks, and signals from proximity sensors. Experiments are conducted to verify the whole system.
Rie Katsuki, Jun Ota 0001, Yusuke Tamura, Takahisa Mizuta, Tomomi Kito, Tamio Arai, Tsuyoshi Ueyama, Tsuyoshi Nishiyama
IROS8
2002 Environmental support method for intelligent robots - movement decision method of robots based on reliability and trial time
abstract
Recently the activity of robots has been remarkable, and robots are branching out into general environment such as home or office. Although robots are active, planners uniquely decide the action method of robots when robots operate missions. Therefore, the most suitable approach is not assured. So, in this report we propose a method that we evaluate robots' actions from the viewpoint of both reliability and time, when robots operate missions. Then we calculate the most suitable approach for robots. To be concrete, by using a diagram we evaluate robots' actions and calculate the most suitable approach. In addition, we evaluate them not from all the actions immediately, but from the action units by making an evaluation index. So, we can shorten the time for evaluation. Finally, we realize the operations by a real robot with the most appropriate approach.
Takahisa Mizuta, Jun Ota 0001, Rie Katsuki, Tamio Arai, Tsuyoshi Ueyama, Tsuyoshi Nishiyama
IROS6
2001 Semi-guided navigation of AGV through iterative learning
abstract
In this paper, the authors aim at realizing an accurate navigation system of automated guided vehicles (AGV). The authors propose a way of estimating positioning error with magnetic tape, which is widely used in a factory as an external sensor. However, flexibility for path relocation is insufficient, because, in general, the tape should be laid down on the floor from a start point to a goal point so that AGV can reach their target. To overcome this inefficiency, the authors firstly propose a semi-guided navigation methodology by means of two kinds of magnetic tapes based on an error analysis. The semi-guided navigation means that magnetic tapes are only placed at the start and the goal points individually. Therefore, this system enables us to remove most of the magnetic tape. Moreover, the authors attempt a fixed model learning to prevent stationary error while AGV run iteratively. Finally, the authors carry out experiments to evaluate and verify the efficiency of the proposed method.
Tomoya Fujimoto, Jun Ota 0001, Tamio Arai, Tsuyoshi Ueyama, Tsuyoshi Nishiyama
IROS5