Our team focuses on point cloud based representation and reasoning techniques for building accurate and meaningful 3D maps for mobile robots in both indoor and outdoor environments. One of our main application and deployment scenario is the Assistive Kitchen. However, all our methods were carefully crafted with generality in mind, therefore they have been also successfully applied to outdoor urban, aerial, and underwater datasets.
This project was partly funded by CoTeSys.
@inproceedings{icra11semantic-perception,
author = {Nico Blodow and Zoltan-Csaba Marton and Dejan Pangercic and Thomas R\"uhr and Moritz Tenorth and Michael Beetz},
title = {Inferring Generalized Pick-and-Place Tasks from Pointing Gestures},
booktitle = {IEEE International Conference on Robotics and Automation (ICRA), Workshop on Semantic Perception, Mapping and Exploration},
month = {May, 9--13},
year = {2011},
bib2html_pubtype = {Workshop Paper},
bib2html_groups = {EnvMod, K4C},
bib2html_funding = {CoTeSys},
bib2html_rescat = {Perception, Representation, Reasoning},
bib2html_domain = {Assistive Household}
}