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Object detection and mapping for service robot tasks

Published online by Cambridge University Press:  01 March 2007

Staffan Ekvall ,
Danica Kragic  and
Patric Jensfelt
Staffan Ekvall*
Affiliation:
Computational Vision and Active Perception Laboratory, Centre for Autonomous Systems, Royal Institute of Technology, Stockholm, Sweden
Danica Kragic
Affiliation:
Computational Vision and Active Perception Laboratory, Centre for Autonomous Systems, Royal Institute of Technology, Stockholm, Sweden
Patric Jensfelt
Affiliation:
Computational Vision and Active Perception Laboratory, Centre for Autonomous Systems, Royal Institute of Technology, Stockholm, Sweden
*
*Corresponding author. E-mail: danik@nada.kth.se
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Summary

The problem studied in this paper is a mobile robot that autonomously navigates in a domestic environment, builds a map as it moves along and localizes its position in it. In addition, the robot detects predefined objects, estimates their position in the environment and integrates this with the localization module to automatically put the objects in the generated map. Thus, we demonstrate one of the possible strategies for the integration of spatial and semantic knowledge in a service robot scenario where a simultaneous localization and mapping (SLAM) and object detection recognition system work in synergy to provide a richer representation of the environment than it would be possible with either of the methods alone. Most SLAM systems build maps that are only used for localizing the robot. Such maps are typically based on grids or different types of features such as point and lines. The novelty is the augmentation of this process with an object-recognition system that detects objects in the environment and puts them in the map generated by the SLAM system. The metric map is also split into topological entities corresponding to rooms. In this way, the user can command the robot to retrieve a certain object from a certain room. We present the results of map building and an extensive evaluation of the object detection algorithm performed in an indoor setting.

Keywords

SLAMActive object recognitionReceptive field color co-occurence histograms
Type
Article
Information
Robotica , Volume 25 , Issue 2 , March 2007 , pp. 175 - 187
Copyright
Copyright © Cambridge University Press 2007

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