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Yoshimitsu Nishizawa

dblp:139/6690 · DBLP profile ↗
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3ranked-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 · 2Applied, interdisciplinary, general and emerging computing · 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
2 papers
Robot navigation and mapping · 76% 3D vision · 21% Motion planning and robot control · 3%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › mobile robot navigation
map-based navigation
0.021995
Map-based navigation for a mobile robot with omnidirectional image sensor COPIS · IEEE Trans. Robotics Autom. 1995
Map based navigation of the mobile robot using omnidirectional image sensor COPIS · ICRA 1992
Robotics › Robot navigation and mapping
localization
0.011995
Map-based navigation for a mobile robot with omnidirectional image sensor COPIS · IEEE Trans. Robotics Autom. 1995
Robotics › Robot navigation and mapping › mobile robot perception › visual sensing
omnidirectional camera
0.011995
Map-based navigation for a mobile robot with omnidirectional image sensor COPIS · IEEE Trans. Robotics Autom. 1995
Computer vision › 3D vision
omnidirectional vision
0.011995
Map-based navigation for a mobile robot with omnidirectional image sensor COPIS · IEEE Trans. Robotics Autom. 1995
Robotics › Robot navigation and mapping
visual navigation
0.011992
Map based navigation of the mobile robot using omnidirectional image sensor COPIS · ICRA 1992
Robotics › Robot navigation and mapping
environment mapping
0.011995
Map-based navigation for a mobile robot with omnidirectional image sensor COPIS · IEEE Trans. Robotics Autom. 1995
Computer vision › 3D vision
map generation
0.011995
Map-based navigation for a mobile robot with omnidirectional image sensor COPIS · IEEE Trans. Robotics Autom. 1995
Robotics › Motion planning and robot control
collision avoidance
0.011992
Map based navigation of the mobile robot using omnidirectional image sensor COPIS · ICRA 1992

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

azimuth matching · 0.0omnidirectional image sensor · 0.0conic mirror · 0.0
YearPublicationVenuePosition
1995 Map-based navigation for a mobile robot with omnidirectional image sensor COPIS
abstract
We designed a new omnidirectional image sensor COPIS (Conic Projection Image Sensor) to guide the navigation of a mobile robot. The feature of COPIS is passive sensing of the omnidirectional image of the environment, in real-time (at the frame rate of a TV camera), using a conic mirror. COPIS is a suitable sensor for visual navigation in a real world environment. We report here a method for navigating a robot by detecting the azimuth of each object in the omnidirectional image. The azimuth is matched with the given environmental map. The robot can precisely estimate its own location and motion (the velocity of the robot) because COPIS observes a 360/spl deg/ view around the robot, even when all edges are not extracted correctly from the omnidirectional image. The robot can avoid colliding against unknown obstacles and estimate locations by detecting azimuth changes, while moving about in the environment. Under the assumption of the known motion of the robot, an environmental map of an indoor scene is generated by monitoring azimuth change in the image.>
Yasushi Yagi, Yoshimitsu Nishizawa, Masahiko Yachida
IEEE Trans. Robotics Autom.2
1992 Map based navigation of the mobile robot using omnidirectional image sensor COPIS
abstract
The authors propose a novel omnidirectional image sensor, COPIS (Conic Projection Image Sensor), for guiding the navigation of a mobile robot. It performs passive sensing of the omnidirectional image of the environment in real time (at the frame rate of a TV camera) using a conic mirror. COPIS is a suitable sensor for visual navigation in the real-world environment with moving objects. The authors describe a method for estimating the location and the motion of the robot by detecting the azimuth of each object in the omnidirectional image. In this method, the azimuth is matched with the given environmental map. They also present a method to avoid collision against unknown obstacles and estimate their locations by detecting their azimuth changes while the robot is moving in the environment. Using the COPIS system, several experiments in the real world were performed.>
Yasushi Yagi, Yoshimitsu Nishizawa, Masahiko Yachida
ICRA2
1991 Estimating location and avoiding collision against unknown obstacles for the mobile robot using omnidirectional image sensor COPIS
abstract
Proposes a new omnidirectional image sensor, COPIS (conic projection image sensor), for guiding navigation of a mobile robot. It features passive sensing of omnidirectional images of the environment in real-time (at the frame rate of a TV camera) using a conic mirror. COPIS is a suitable sensor for visual navigation in real world environment with moving objects. The paper describes a method for estimating the location and the motion of the robot by detecting the azimuth of each object in the omnidirectional image. It also presents a method to avoid collision against unknown obstacles and estimates their locations by detecting their azimuth changes while the robot is moving in the environment.>
Yasushi Yagi, Yoshimitsu Nishizawa, Masahiko Yachida
IROS2