Tracing Commodities in Indoor Environments for Service Robotics

@inproceedings{Mozos2012TracingCI,
  title={Tracing Commodities in Indoor Environments for Service Robotics},
  author={{\'O}scar Mart{\'i}nez Mozos and François Chollet and Kouji Murakami and Ken'ichi Morooka and Tokuo Tsuji and Ryo Kurazume and Tsutomu Hasegawa},
  booktitle={SyRoCo},
  year={2012}
}
Abstract Daily life assistance for elderly people is one of the most promising scenarios for service robots in the near future. In particular, the go-and-fetch task will be one of the most demanding tasks in these cases. In this paper, we present an informationally structured room that supports a service robot in the task of daily object fetching. Our environment contains different distributed sensors including a floor sensing system and several intelligent cabinets. Sensor information is sent… 
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Methods Citations
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3 Citations

Integrating planning perception and action for informed object search
TLDR
This paper describes how machine learning techniques can be used to decide which places should be inspected first, based on images that the robot acquires passively, and provides quantitative results comparing the efficiency of the proposed method and two base approaches.
Object classification with metric and semantic inference
TLDR
A holistic and developable inference method based on a generalized directional Markov random field that makes use of 3D surface features, intrinsic object parts relations, metric data and semantic relations with other observed objects to improve the results of object classification compared to the feature-only approach.
Object Classification Using Dempster–Shafer Theory
TLDR
A new method of complex object recognition and classification by a mobile robot that allows to make use not only of object features, but also of information about sensor uncertainty, possible occlusions and can handle contradictory evidence in an integral way is presented.

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