Author
Thomas Röfer
Other affiliations: German Research Centre for Artificial Intelligence
Bio: Thomas Röfer is an academic researcher from University of Bremen. The author has contributed to research in topics: Robot & Humanoid robot. The author has an hindex of 27, co-authored 86 publications receiving 1979 citations. Previous affiliations of Thomas Röfer include German Research Centre for Artificial Intelligence.
Topics: Robot, Humanoid robot, Mobile robot, Wheelchair, Machine vision
Papers published on a yearly basis
Papers
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TL;DR: The Bremen autonomous wheelchair implements obstacle avoidance plus driving and routing assistance in a shared-control system that solves the tasks of reliably detecting obstacles in the environment and safely avoiding these obstructions.
Abstract: The Bremen autonomous wheelchair implements obstacle avoidance plus driving and routing assistance in a shared-control system. This article shows how the tasks of reliably detecting obstacles in the environment and safely avoiding these obstructions are solved.
130 citations
10 Nov 2003
TL;DR: This paper presents a fast approach for vision-based self-localization in RoboCup that extracts the features required for localization without processing the whole image and is a fist step towards independence of lighting conditions.
Abstract: This paper presents a fast approach for vision-based self-localization in RoboCup. The vision system extracts the features required for localization without processing the whole image and is a fist step towards independence of lighting conditions. In the field of self-localization, some new ideas are added to the well-known Monte Carlo localization approach that increase both stability and reactivity, while keeping the processing time low.
121 citations
01 Jan 2006
TL;DR: SimRobot as discussed by the authors is a 3D robot simulator based on rigid body dynamics, which includes a physical model which is based on a rigid body model and includes a variety of different generic bodies, sensors and actuators.
Abstract: This paper describes SimRobot, a robot simulator which is able to simulate arbitrary user-defined robots in three-dimensional space. It includes a physical model which is based on rigid body dynamics. To allow an extensive flexibility in building accurate models, a variety of different generic bodies, sensors and actuators has been implemented. Furthermore, the simulator follows an user-oriented approach by including several mechanisms for visualization, direct actuator manipulation, and interaction with the simulated world. To demonstrate the general approach, this paper presents multiple examples of different robots which have been simulated so far.
114 citations
Journal Article•
TL;DR: SimRobot, a robot simulator which is able to simulate arbitrary user-defined robots in three-dimensional space, is described, which includes a physical model which is based on rigid body dynamics.
Abstract: This paper describes SimRobot, a robot simulator which is able to simulate arbitrary user-defined robots in three-dimensional space. It includes a physical model which is based on rigid body dynamics. To allow an extensive flexibility in building accurate models, a variety of different generic bodies, sensors and actuators has been implemented. Furthermore, the simulator follows an user-oriented approach by including several mechanisms for visualization, direct actuator manipulation, and interaction with the simulated world. To demonstrate the general approach, this paper presents multiple examples of different robots which have been simulated so far.
104 citations
10 Oct 2009
TL;DR: The combination of a non-invasive EEG-based human-robot interface and an autonomous navigation system that safely executes the issued commands is proposed, allowing severely disabled people who cannot move their arms and legs to steer an automated wheelchair.
Abstract: In order to allow severely disabled people who cannot move their arms and legs to steer an automated wheelchair, this work proposes the combination of a non-invasive EEG-based human-robot interface and an autonomous navigation system that safely executes the issued commands. The robust classification of steady-state visual evoked potentials in brain activity allows for the seamless projection of qualitative directional navigation commands onto a frequently updated route graph representation of the environment. The deduced metrical target locations are navigated to by the application of an extended version of the well-established Nearness Diagram Navigation method. The applicability of the system proposed is demonstrated by a real-world pilot study in which eight out of nine untrained subjects successfully navigated an automated wheelchair, requiring only some ten minutes of preparation.
97 citations
Cited by
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TL;DR: In this paper, the authors offer a new book that enPDFd the perception of the visual world to read, which they call "Let's Read". But they do not discuss how to read it.
Abstract: Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd the perception of the visual world to read.
2,250 citations
Book•
20 May 2005
TL;DR: In this paper, the mathematical underpinnings of robot motion are discussed and a text that makes the low-level details of implementation to high-level algorithmic concepts is presented.
Abstract: A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts. Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on circuit boards, directing digital actors in computer graphics, robot-assisted surgery and medicine, and in novel areas such as drug design and protein folding. This text reflects the great advances that have taken place in the last ten years, including sensor-based planning, probabalistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, rleating low-level implementation details to high-level algorithmic concepts.
1,811 citations
868 citations