AMOS: comparison of scan matching approaches for self-localization in indoor environments

@article{Gutmann1996AMOSCO,
  title={AMOS: comparison of scan matching approaches for self-localization in indoor environments},
  author={J.-S. Gutmann and Christian Schlegel},
  journal={Proceedings of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT '96)},
  year={1996},
  pages={61-67}
}
  • J.-S. GutmannC. Schlegel
  • Published 9 October 1996
  • Computer Science
  • Proceedings of the First Euromicro Workshop on Advanced Mobile Robots (EUROBOT '96)
This paper describes results from evaluating different self-localization approaches in indoor environments for mobile robots. [] Key Method To fulfil these requirements we made some extensions to the existing approaches and combined them in a suitable manner. Real world experiments with our robot within the everyday environment of our institute show that the position error can be kept small enough to perform navigation tasks.

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References

SHOWING 1-6 OF 6 REFERENCES

Shape registration using optimization for mobile robot navigation

  • F. Lu
  • Computer Science
  • 1995
This thesis proposes two iterative scan matching algorithms which do not require feature extraction or segmentation and forms an optimal procedure to combine all available spatial relations to resolve possible map inconsistency.

Blanche-an experiment in guidance and navigation of an autonomous robot vehicle

  • I. Cox
  • Engineering
    IEEE Trans. Robotics Autom.
  • 1991
Blanche's position estimation system consists of a priori map of its environment and a robust matching algorithm that estimates the precision of the corresponding match/correction that is then optimally combined with the current odometric position to provide an improved estimate of the vehicle's position.

Simultaneous localisation and map building for autonomous guided vehicles

  • S. BorthwickH. Durrant-Whyte
  • Computer Science
    Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)
  • 1994
A multi-track extendedKalman filter navigation system which offers real time localisation while simultaneously constructing a map consisting of geometric features, each in turn described by an extended Kalman filter is described.

AMOS; active perception of an autonomous system

  • M. KnickC. Schlegel
  • Computer Science
    Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)
  • 1994
An architecture which integrates both symbolic planning as well as nonsymbolic reactive mechanisms, thus providing a basic autonomy, so that the robot can freely maneuver around without any detailed model of itself and its complex real-world environment is presented.

Integration of Sub-Symbolic and Symbolic Information Processing in Robot Control

  • M. KnickF. Radermacher
  • Computer Science
    Proceedings of the Third Annual Conference of AI, Simulation, and Planning in High Autonomy Systems 'Integrating Perception, Planning and Action'.
  • 1992
In the Autonomous m b i l e Systems project, the FAW uses a mobile robot to study questions related to the integration of sub-symbolic and symbolic information processing, and demonstrates the ability to generate concepts carrying semantics in a static environment using a simple organizing principle: spatial neighborhood in images.

Optimal global pose estimation for consistent sensor data registration

  • F. LuE. Milios
  • Mathematics
    Proceedings of 1995 IEEE International Conference on Robotics and Automation
  • 1995
This work considers the problem of consistent range data registration in modeling an unknown environment as the optimal estimation of pose variables under the maximum likelihood criterion and derives closed-form pose estimates as well as their covariance matrices.