Semantic mapping for service robots: building and using maps for mobile manipulators in semi-structured environments

Simultaneous Localization and Mapping;SLAM;Robotic mapping;Semantic mapping;Robotic perception;Service robots

Trevor, Alexander J. B. ; Christensen, Henrik I. Interactive Computing Dellaert, Frank Fox, Dieter Howard, Ayanna M. Rehg, James ; Christensen, Henrik I.

University:Georgia Institute of Technology

Department:Interactive Computing

关键词: Simultaneous Localization and Mapping;    SLAM;    Robotic mapping;    Semantic mapping;    Robotic perception;    Service robots;   

Others  :  https://smartech.gatech.edu/bitstream/1853/53583/1/TREVOR-DISSERTATION-2015.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Although much progress has been made in the field of robotic mapping, many challenges remain including: efficient semantic segmentation using RGB-D sensors, map representations that include complex features (structures and objects), and interfaces for interactive annotation of maps. This thesis addresses how prior knowledge of semi-structured human environments can be leveraged to improve segmentation, mapping, and semantic annotation of maps.We present an organized connected component approach for segmenting RGB-D data into planes and clusters.These segments serve as input to our mapping approach that utilizes them as planar landmarks and object landmarks for Simultaneous Localization and Mapping (SLAM), providing necessary information for service robot tasks and improving data association and loop closure.These features are meaningful to humans, enabling annotation of mapped features to establish common ground and simplifying tasking.A modular, open-source software framework, the OmniMapper, is also presented that allows a number of different sensors and features to be combined to generate a combined map representation, and enabling easy addition of new feature types.