Koike, C and Pradalier, C and Bessiere, P and Mazer, E (2003) Obstacle Avoidance and Proscriptive Bayesian Programming. [Conference Paper]
Full text available as:
![]()
|
PDF
193Kb |
Abstract
Unexpected events and not modeled properties of the robot environment are some of the challenges presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a probabilistic approach called Bayesian Programming, which aims to deal with the uncertainty, imprecision and incompleteness of the information handled to solve the obstacle avoidance problem. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. A video illustration of the developed experiments can be found at http://www.inrialpes.fr/sharp/pub/laplace
Item Type: | Conference Paper |
---|---|
Keywords: | Bayesian programming, Obstacle avoidance, Command fusion |
Subjects: | Computer Science > Robotics |
ID Code: | 3756 |
Deposited By: | malrait, Olivier |
Deposited On: | 10 Aug 2004 |
Last Modified: | 11 Mar 2011 08:55 |
Metadata
- ASCII Citation
- Atom
- BibTeX
- Dublin Core
- EP3 XML
- EPrints Application Profile (experimental)
- EndNote
- HTML Citation
- ID Plus Text Citation
- JSON
- METS
- MODS
- MPEG-21 DIDL
- OpenURL ContextObject
- OpenURL ContextObject in Span
- RDF+N-Triples
- RDF+N3
- RDF+XML
- Refer
- Reference Manager
- Search Data Dump
- Simple Metadata
- YAML
Repository Staff Only: item control page