The research theme of this dissertation is the multiple-vehicles cooperative perception (or cooperative perception) applied in the context of intelligent vehicle systems. The general methodology of the presented works in this dissertation is to realize multiple-intelligent vehicles cooperative perception, which aims at providing better vehicle perception result compared with single vehicle perception (or non-cooperative perception). Instead of focusing our research works on the absolute performance of cooperative perception, we focus on the general mechanisms which enable the realization of cooperative localization and cooperative mapping (and moving objects detection), considering that localization and mapping are two underlying tasks for an intelligent vehicle system. We also exploit the possibility to realize certain augmented reality effect with the help of basic cooperative perception functionalities; we name this kind of practice as cooperative augmented reality. Naturally, the contributions of the presented works consist in three aspects: cooperative localization, cooperative local mapping and moving objects detection, and cooperative augmented reality.
Identifer | oai:union.ndltd.org:CCSD/oai:pastel.archives-ouvertes.fr:pastel-00766986 |
Date | 21 September 2012 |
Creators | Li, Hao |
Publisher | Ecole Nationale Supérieure des Mines de Paris |
Source Sets | CCSD theses-EN-ligne, France |
Language | English |
Detected Language | English |
Type | PhD thesis |
Page generated in 0.0016 seconds