Summary
Modeling the environment is crucial for a mobile robot. Common approaches use Bayesian filters like particle filters, Kalman filters and their extended forms. We present an alternative and supplementing approach using constraint techniques based on spatial constraints between object positions. This yields several advantages: a) the agent can choose from a variety of belief functions, b) the computational complexity is decreased by efficient algorithms. The focus of the paper are constraint propagation techniques under the special requirements of navigation tasks.
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Göhring, D., Mellmann, H., Burkhard, HD. (2008). Constraint Based Object State Modeling. In: Bruyninckx, H., Přeučil, L., Kulich, M. (eds) European Robotics Symposium 2008. Springer Tracts in Advanced Robotics, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78317-6_7
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DOI: https://doi.org/10.1007/978-3-540-78317-6_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78315-2
Online ISBN: 978-3-540-78317-6
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