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

Orhan Engin

dblp:87/4249 · DBLP profile ↗
← Back
3ranked-venue papers
1as first author
0since 2021 · last 2009
0000-0002-7250-0317ORCID · corroborated

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2 · 1 first-author

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 navigation and mapping · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › mobile robot navigation › sensor-based navigation
LiDAR-based navigation
0.112009
Laser-based navigation enhanced with 3D time-of-flight data · ICRA 2009
Robotics › Robot navigation and mapping
obstacle avoidance
0.112009
Laser-based navigation enhanced with 3D time-of-flight data · ICRA 2009
Robotics › Robot navigation and mapping
sensor fusion
0.112009
Laser-based navigation enhanced with 3D time-of-flight data · ICRA 2009

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

virtual laser · 0.1extrinsic sensor calibration · 0.1
YearPublicationVenuePosition
2009 Laser-based navigation enhanced with 3D time-of-flight data
abstract
Navigation and obstacle avoidance in robotics using planar laser scans has matured over the last decades. They basically enable robots to penetrate highly dynamic and populated spaces, such as people's home, and move around smoothly. However, in an unconstrained environment the two-dimensional perceptual space of a fixed mounted laser is not sufficient to ensure safe navigation. In this paper, we present an approach that pools a fast and reliable motion generation approach with modern 3D capturing techniques using a time-of-flight camera. Instead of attempting to implement full 3D motion control, which is computationally more expensive and simply not needed for the targeted scenario of a domestic robot, we introduce a ldquovirtual laserrdquo. For the originally solely laser-based motion generation the technique of fusing real laser measurements and 3D point clouds into a continuous data stream is 100% compatible and transparent. The paper covers the general concept, the necessary extrinsic calibration of two very different types of sensors, and exemplarily illustrates the benefit which is to avoid obstacles not being perceivable in the original laser scan.
Agnes Swadzba, Roland Philippsen, Orhan Engin, Marc Hanheide, Sven Wachsmuth
ICRA4
2009 Information systems outsourcing decisions using a group decision-making approach
Cengiz Kahraman, Orhan Engin, Özgür Kabak, Ihsan Kaya
Eng. Appl. Artif. Intell.2
2004 A new approach to solve hybrid flow shop scheduling problems by artificial immune system
Orhan Engin, Alper Döyen
Future Gener. Comput. Syst.1