Authors: Murat Arslan
In this thesis, obstacle detection via image of objects and then pathfinding problems of NAO humanoid robot is considered. NAO's camera is used to capture the images of world map. The captured image is processed and classified into two classes; area with obstacles and area without obstacles. For classification of images, Support Vector Machine (SVM) is used. After classification the map of world is obtained as area with obstacles and area without obstacles. This map is input for path finding algorithm. In the thesis A* path finding algorithm is used to find path from the start point to the goal. The aim of this work is to implement a support vector machine based solution to robot guidance problem, visual path planning and obstacle avoidance. The used algorithms allow to detect obstacles and find an optimal path. The thesis describe basic steps of navigation of mobile robots.
Comments: 116 Pages.
[v1] 2017-05-02 21:38:43
Unique-IP document downloads: 118 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.