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On the impact of the camera field-of-view to Direct Visual Servoing robot trajectories when using the Photometric Gaussian Mixtures as dense feature

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  • معلومة اضافية
    • Contributors:
      Joint Robotics Laboratory (CNRS-AIST JRL); National Institute of Advanced Industrial Science and Technology (AIST)-Centre National de la Recherche Scientifique (CNRS); Connaissance et Intelligence Artificielle Distribuées Dijon (CIAD); Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB); Modélisation, Information et Systèmes - UR UPJV 4290 (MIS); Université de Picardie Jules Verne (UPJV)
    • بيانات النشر:
      CCSD
    • الموضوع:
      2025
    • الموضوع:
      Munich; Germany
    • نبذة مختصرة :
      International audience ; This paper studies the impact of cameras with different fields of view (FoV) on Direct Visual Servoing to control robot motions from pixel intensities. Focusing on the Photometric Gaussian Mixture Visual Servoing that showed great convergence domains, this paper investigates two types of FoV: the seminal perspective case and the novel full om- nidirectional case. Implemented with our open-source generic software framework libPeR for a fair comparison, the Visual Servoing experiments on a 6 degrees-of-freedom robot arm provide an in-depth evaluation of the impact of each FoV on the convergence domain, straightness of the trajectory and time to reach convergence.
    • الدخول الالكتروني :
      https://hal.science/hal-04810271
      https://hal.science/hal-04810271v1/document
      https://hal.science/hal-04810271v1/file/2025_SII_Schulte.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.3AF2FE40