Abstract

Pose estimation is a technique used to predict the pose of an object, i.e., its orientation and its position. This technique is needed by the robot to pick up objects that are placed somewhere. In general, this technique is developed with visual input from a camera. The challenge that is usually faced in this technique is the lighting conditions that are not fixed, where the stability of the estimation results in this environment is highly expected. In this study, we first use an RGB-D-NIR camera to provide color (RGB), depth (D), and near-infrared (NIR) inputs which are expected to complement each other. Second, by utilizing data from the camera, we combine it with Guided Filtering Fusion and Deep learning methods. As a preliminary result of the study, we conducted experiments in normal and dark lightning conditions on household objects, with various input combinations; and obtained quite accurate results in dark conditions.

Original languageEnglish
Title of host publication2023 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationLeveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages216-221
Number of pages6
ISBN (Electronic)9798350313956
DOIs
Publication statusPublished - 2023
Event24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023 - Hybrid, Surabaya, Indonesia
Duration: 26 Jul 202327 Jul 2023

Publication series

Name2023 International Seminar on Intelligent Technology and Its Applications: Leveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding

Conference

Conference24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023
Country/TerritoryIndonesia
CityHybrid, Surabaya
Period26/07/2327/07/23

Keywords

  • NIR camera
  • RGBD camera
  • household object
  • pose estimation

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