In this paper, we present a framework for doing localization from distance measurements, given an estimate of the local motion. We show how we can register the local motion of a receiver, to a global coordinate system, using trilateration of given distance measurements from the receivers to senders in known positions. We describe how many different motion models can be formulated within the same type of registration framework, by only changing the transformation group. The registration is based on a test and hypothesis framework, such as RANSAC, and we present novel and fast minimal solvers that can be used to bootstrap such methods. The system is tested on both synthetic and real data with promising results.

Original languageEnglish
Title of host publication2022 25th International Conference on Information Fusion, FUSION 2022
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781737749721
Publication statusPublished - 2022
Event25th International Conference on Information Fusion, FUSION 2022 - Linkoping, Sweden
Duration: 2022 Jul 42022 Jul 7


Conference25th International Conference on Information Fusion, FUSION 2022

Subject classification (UKÄ)

  • Computer Vision and Robotics (Autonomous Systems)

Free keywords

  • IMU
  • minimal solvers
  • motion model
  • odometry
  • time-of-arrival
  • Trilateration


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