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Cognitive SLAM
PrjCFUMax 20  +
PrjCFUMin 5  +
PrjDescription We have developed a system that is able to We have developed a system that is able to detect, recognize and track objects in an image taken from a low cost robot equipped with a IMU and a low cost camera. The system is capable to detect and recognize objects using a user defined fuzzy tree classifier. However the system performance is heavily dependent on high level feature extraction, such as geometric features. The problem is non trivial due to noisy low cost camera and changes in the light conditions. The aim of this project is to improve the feature extraction and description process, both in performance and quality, possible adding a more complete description or others type of features. The long term aim of the research is to have an autonomuos robot capable to create a semantic map of the envirorment, localize himself , make inference on the map, navigate into the envirorment using the objects as landmarks. No special skills are required, except basic c and object oriented programming. t basic c and object oriented programming.
PrjImage Image:C_SLAM_Recognition2.png  +
PrjLevel Master of Science +
PrjResArea Robotics +
PrjResTopic SLAM + , Feature Extraction +
PrjStarts 1 January 2015  +
PrjStatus Active  +
PrjStudMax 2  +
PrjStudMin 1  +
PrjTitle Cognitive SLAM  +
PrjTutor User:AndreaBonarini + , User:DavideTateo +
PrjType Course + , Thesis +
Categories ProjectProposal  +
Modification dateThis property is a special property in this wiki. 18 December 2014 00:10:28  +
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