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Computer Science > Robotics

arXiv:2108.07265 (cs)
[Submitted on 16 Aug 2021 (v1), last revised 14 Oct 2022 (this version, v4)]

Title:The Integrated Probabilistic Data Association Filter Adapted to Lie Groups

Authors:Mark E. Petersen, Randal W. Beard
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Abstract:The Integrated Probabilistic Data Association Filter (IPDAF) is a target tracking algorithm based on the Probabilistic Data Association Filter that calculates a statistical measure that indicates if an estimated representation of the target properly represents the target or is generated from non-target-originated measurements. The main contribution of this paper is to adapt the IPDAF to constant velocity target models that evolve on connected, unimodular Lie groups, and where the measurements are also defined on a Lie group. We present an example where the methods developed in the paper are applied to the problem of tracking a ground vehicle on the special Euclidean group SE(2).
Comments: 21 pages, 10 figures, 1 table will be submitted
Subjects: Robotics (cs.RO)
Cite as: arXiv:2108.07265 [cs.RO]
  (or arXiv:2108.07265v4 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2108.07265

Submission history

From: Mark Petersen [view email]
[v1] Mon, 16 Aug 2021 17:59:34 UTC (687 KB)
[v2] Tue, 24 Aug 2021 14:10:31 UTC (687 KB)
[v3] Thu, 24 Mar 2022 00:07:27 UTC (1,143 KB)
[v4] Fri, 14 Oct 2022 21:04:55 UTC (1,301 KB)
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