Publications:Sensor Based Adaptive Metric-Topological Cell Decomposition Method for Semantic Annotation of Structured Environments

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Title Sensor Based Adaptive Metric-Topological Cell Decomposition Method for Semantic Annotation of Structured Environments
Author Saeed Gholami Shahbandi and Björn Åstrand and Roland Philippsen
Year 2014
PublicationType Conference Paper
Journal
HostPublication 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV)
Conference 13th International Conference on Control, Automation, Robotics and Vision, ICARCV 2014, Marina Bay Sands, Singapore, December 10-12, 2014
DOI http://dx.doi.org/10.1109/ICARCV.2014.7064584
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:750189
Abstract A fundamental ingredient for semantic labeling is a reliable method for determining and representing the relevant spatial features of an environment. We address this challenge for planar metric-topological maps based on occupancy grids. Our method detects arbitrary dominant orientations in the presence of significant clutter, fits corresponding line features with tunable resolution, and extracts topological information by polygonal cell decomposition. Real-world case studies taken from the target application domain (autonomous forklift trucks in warehouses) demonstrate the performance and robustness of our method, while results from a preliminary algorithm to extract corridors, and junctions, demonstrate its expressiveness. Contribution of this work starts with the formulation of metric-topological surveying of environment, and a generic n-direction planar representation accompanied with a general method for extracting it from occupancy map. The implementation also includes some semantic labels specific to warehouse like environments. © 2014 IEEE.