| 1. |
- Gritti, Marco, et al.
(author)
-
A self-configuration mechanism for software components distributed in an ecology of robots
- 2008
-
In: Intelligent Autonomous Systems 10. - Amsterdam : IOS Press. - 9781586038878 ; , s. 100-109
-
Conference paper (peer-reviewed)abstract
- Distributed heterogeneous robotic systems are often organized in component-based software architectures. The strong added value of these systems comes from their potential ability to dynamically self-configure the interactions of their components, in order to adapt to new tasks and unforeseen situations. However, no satisfactory solutions exist to the problem of automatic self-configuration. We propose a self-configuration mechanism where a special component generates, establishes and monitors the system configurations. We illustrate our approach on a distributed robotic system, and show an experiment in which the configuration component dynamically changes the configuration in response to a component failure.
|
|
| 2. |
- Sjöö, Kristoffer, et al.
(author)
-
Object Localization using Bearing Only Visual Detection
- 2008
-
In: Intelligent Autonomous Systems 10, IAS 2008AS-10. - AMSTERDAM : I O S PRESS. - 9781586038878 ; , s. 254-263
-
Conference paper (peer-reviewed)abstract
- This work demonstrates how an autonomous robotic platform can use intrinsically noisy, coarse-scale visual methods lacking range information to produce good estimates of the location of objects, by using a map-space representation for weighting together multiple observations from different vantage points. As the robot moves through the environment it acquires visual images which are processed by means of a fast but noisy visual detection algorithm that gives bearing only information. The results from the detection are projected from image space into map space, where data from multiple viewpoints can intrinsically combine to yield an increasingly accurate picture of the location of objects. This method has been implemented and shown to work for object localization on a real robot. It has also been tested extensively in simulation, with systematically varied false positive and false negative detection rates. The results demonstrate that this is a viable method for object localization, even under a wide range of sensor uncertainties.
|
|
