Autonomous vehicles navigation on external unstructured terrains based in computer vision

Author(s)

Rafael Luiz Klaser

• Document type: Master's Dissertation
• Press: São Carlos.
• Institution: Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB)
• Defense date: 2014-06-06

Examining board members

Fernando Santos Osório; Moacir Pereira Ponti Junior; Josue Junior Guimarães Ramos

• Advisor: Fernando Santos Osório

Abstract

This work presents a system for autonomous vehicle navigation focusing on unstructured environments, with the primary goal applications in open fields with sparse vegetation, unstructured environments and agricultural scenario. Computer vision is applied as the main perception system using a stereo camera in a car-like vehicle with Ackermann kinematic model. Navigation is performed deliberatively using a path planner based on a lattice state space over a cost map with localization by odometry and GPS. The cost map is obtained through a probabilistic occupation model developed making use of an OctoMap. It is described a sensor model to update the spatial occupancy information of the OctoMap from a point cloud obtained by stereo vision. The points are segmented and filtered taking into account the noise inherent in the image acquisition and calculation of disparity to obtain the distance from points. Tests are performed in simulation, allowing replication and repetition of experiments. The modeling of the vehicle is described to be used in the Gazebo physics simulator in accordance with the real platform CaRINA I (LRM-ICMC/USP automated electrical vehicle) taking into account the kinematic model and the limitations of this vehicle. The development is based on ROS (Robot Operating System) and its basic navigation architecture is customized. System validation is performed on real environment in scenarios with different obstacles and uneven terrain. The system shows satisfactory performance considering a simple configuration and an approach based on only one stereo camera. This dissertation presents the main components of an autonomous navigation system and the necessary steps for its conception as well as results of experiments in simulated and using a real autonomous vehicle (AU)

• FAPESP's process: 12/04555-4 - Autonomous vehicle navigation in outdoor and off-road environments based on computer vision
• Grantee: Rafael Luiz Klaser
• Support Opportunities: Scholarships in Brazil - Master