A sensor fusion framework for wearable sensor suites - Archive ouverte HAL Access content directly
Journal Articles SN Applied Sciences Year : 2021

A sensor fusion framework for wearable sensor suites

Maxime Vaidis
  • Function : Author
  • PersonId : 1096350
François Pomerleau
  • Function : Author
  • PersonId : 1096351


We present a generalized mapping framework that can withstand the challenges incurred by working in unstructured outdoor environments, such as a snowy forest. The proposed method takes advantage of a sensor fusion scheme, where sensors such as cameras and lidars are used in order to reconstruct the surrounding natural environment. Although mapping techniques such as SLAM and ICP cannot themselves properly handle the complexity of natural scenes, they do have the potential to contribute to the global solution in a proposed sensor fusion scheme, based on a factor graph architecture. In this paper, we propose an innovative map registration scheme for visual maps, and show how it can improve the reconstruction quality after data fusion. We also analyze the behavior and sensitivity of factor graphs to uncertainties, by comparing the residual error with different parameter combinations such as variances, using an exhaustive grid search with ground truth comparison. Finally, we suggest an ICP-inferred loop closure, capable of compensating position and attitude drift. The experiments are carried out by recording in a snowy forest using a wearable sensor suite. In the experiments, ground truth was acquired using a millimeter-accurate total station. The proposed framework is shown to be robust and likewise capable of providing estimates that are otherwise unattainable using classic techniques, such as visual SLAM and ICP for lasers. Finally, a visible improvement in the map reconstruction quality is shown, and the proposed framework achieves a translation error of 0.36 meters.
Fichier principal
Vignette du fichier
SN_Applied_Sciences.pdf (16.07 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03201502 , version 1 (18-04-2021)


  • HAL Id : hal-03201502 , version 1


Georges Chahine, Maxime Vaidis, François Pomerleau, Cédric Pradalier. A sensor fusion framework for wearable sensor suites. SN Applied Sciences, In press. ⟨hal-03201502⟩


86 View
7 Download


Gmail Facebook X LinkedIn More