Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Jens-Steffen Gutmann"'
Publikováno v:
Robotics and Autonomous Systems. 62:1248-1258
Vector field SLAM is a framework for localizing a mobile robot in an unknown environment by learning the spatial distribution of continuous signals such as those emitted by WiFi or active beacons. In our previous work we showed that this approach is
Publikováno v:
IEEE Transactions on Robotics. 28:650-667
Localization in unknown environments using low-cost sensors on embedded hardware is challenging. Yet, it is a requirement for consumer robots if systematic navigation is desired. In this paper, we present a localization approach that learns the spati
Publikováno v:
The International Journal of Robotics Research. 27:1117-1134
A humanoid robot that can go up and down stairs, crawl underneath obstacles or simply walk around requires reliable perceptual capabilities for obtaining accurate and useful information about its surroundings. In this work we present a system for gen
Publikováno v:
IFAC Proceedings Volumes. 37:758-763
Segmenting range images into planar regions is an important technique for many applications including mobile robot navigation. We present an efficient method for precise segmentation of stereo range images into multiple planar regions. The method is
Autor:
Mario E. Munich, James Philip Case, Dhiraj Goel, Michael J. Dooley, Daniele Tamino, Paolo Pirjanian, Jens-Steffen Gutmann
Publikováno v:
IROS
We address the problem of systematically covering all accessible floor space in an unknown environment by a mobile robot. Our approach uses rectangular regions that are swept across the environment. In the first stage, the robot covers each region us
Publikováno v:
TePRA
Localization is very helpful for goal-oriented navigation of a mobile robot. In this article, we describe the challenges we faced when designing a low-cost indoor localization system that can be employed on consumer and domestic robots for the system
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783642339318
IAS (2)
IAS (2)
Vector Field SLAM is a method for localizing a mobile robot in an unknown environment from continuous signals such as WiFi or active beacons. Disclosed is a technique for localizing a robot in relatively large and/or disparate areas. This is achieved
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70abf5041bc50a7ccf11b393e0fffaca
https://doi.org/10.1007/978-3-642-33932-5_9
https://doi.org/10.1007/978-3-642-33932-5_9
Publikováno v:
ARSO
Mint is an automatic cleaning robot that sweeps and mops hard-surface floors using dusting and mopping cloths. Thanks to the Northstar navigation technology it systematically cleans and navigates in people's homes. Since it first became commercially
Publikováno v:
Robotics: Science and Systems
The constraints of a low-cost consumer product pose a major challenge for designing a localization system. In previous work, we introduced Vector Field SLAM [5], a system for simultaneously estimating robot pose and a vector field induced by stationa
Publikováno v:
ICRA
Localization in unknown environments using low-cost sensors remains a challenge. This paper presents a new localization approach that learns the spatial variation of an observed continuous signal. We model the signal as a piece-wise linear function a