Hypermaps - Beyond occupancy grids
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Sähkötekniikan korkeakoulu |
Master's thesis
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Authors
Date
2019-08-19
Department
Major/Subject
Space Robotics and Automation
Mcode
ELEC3047
Degree programme
Erasmus Mundus Space Master
Language
en
Pages
51
Series
Abstract
Intelligent and autonomous robotic applications often require robots to have more information about their environment than provided by traditional occupancy maps. An example are semantic maps, which provide qualitative descriptions of the environment. While research in the area of semantic mapping has been performed, most robotic frameworks still offer only occupancy maps. In this thesis, a framework is developed to handle multi-layered 2D maps in ROS. The framework offers occupancy and semantic layers, but can be extended with new layer types in the future. Furthermore, an algorithm to automatically generate semantic maps from RGB-D images is presented. Software tests were performed to check if the framework fulfills all set requirements. It was shown that the requirements are accomplished. Furthermore, the semantic mapping algorithm was evaluated with different configurations in two test environments, a laboratory and a floor. While the object shapes of the generated semantic maps were not always accurate and some false detections occurred, most objects were successfully detected and placed on the semantic map. Possible ways to improve the accuracy of the mapping in the future are discussed.Description
Supervisor
Kyrki, VilleThesis advisor
Verdoja, FrancescoKeywords
hypermaps, semantic maps, object detection, mapping