Paper Info
Title
Simulation of an Autonomous Vehicle with a Vision-Based Navigation System in Unstructured Terrains Using OctoMap
Abstract
Design and implementation of autonomous vehicles is a very complex task. One important step on building autonomous navigation systems is to apply it first on simulations. We present here a vision-based autonomous navigation approach in unstructured terrains for a car-like vehicle. We modeled the vehicle and the scenario in a realistic physics simulation with the same constraints of a real car and uneven terrain with vegetation. We use stereo vision to build a navigation cost map grid based on a probabilistic occupancy space represented by an OctoMap. The localization is based on GPS and compass integrated with wheel odometry. A global planning is performed and continuously updated with the information added to the cost map while the vehicle moves. In our simulations we could autonomously navigate the vehicle through obstructed spaces avoiding collisions and generating feasible trajectories. This system will be validated in the near future using our autonomous vehicle testing platform - CaRINA
Year
DOI
Venue
2013
10.1109/SBESC.2013.46
SBESC
Keywords
Field
DocType
navigation, stereo vision, octomap, simulation,probabilistic logic,navigation,stereo vision,simulation,modeling
Computer vision,Grid reference,Dynamical simulation,Compass,Stereopsis,Navigation system,Odometry,Artificial intelligence,Global Positioning System,Mobile robot navigation,Geography
Conference
ISSN
Citations 
PageRank 
2324-7886
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Rafael Luiz Klaser100.34
Fernando Santos Osório211419.08
Denis Fernando Wolf3479.86