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3D-Position Tracking and Control for All-Terrain Robots
Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. This book demonstrates how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. In this work, a mechanical structure allowing smooth motion across obstacles with limited wheel slip is used. In particular, it enables the use of odometry and inertial sensors to improve the position estimation in rough terrain. A method for computing 3D motion increments based on the wheel encoders and chassis state sensors is developed. The algorithm runs online and can be adapted to any kind of passive wheeled rover. Finally, sensor fusion using 3D-Odometry, inertial sensors and visual motion estimation based on stereovision is presented. The experimental results demonstrate how each sensor contributes to increase the accuracy and robustness of the 3D position estimation.
3D design reconstruction
This report will talk about a way to design and rebuild a cheap, true-to-the-truth 3D system using reverse engineering. The system provides the service of reconstructing objects into 3D models by placing the object in a predetermined place facing a set of sensors and cameras at a certain distance and at precise angles, using the angle of rotation for each image and combining the points of triangulation we can build a form of 3D modeling types. These models can be used in digital animation or printed with 3D printers for a wide variety of applications.
