Pose invariant people detection in point clouds for mobile robots


Hacinecipoglu A. , Konukseven E. İ. , Koku A. B.

International Journal of Mechanical Engineering and Robotics Research, cilt.9, ss.709-715, 2020 (Diğer Kurumların Hakemli Dergileri) identifier

  • Cilt numarası: 9
  • Basım Tarihi: 2020
  • Doi Numarası: 10.18178/ijmerr.9.5.709-715
  • Dergi Adı: International Journal of Mechanical Engineering and Robotics Research
  • Sayfa Sayıları: ss.709-715

Özet

To be able to navigate in socially complaint fashion and safely, people detection is a very important ability for robots deployed in our social environments. However, it is a challenging task since humans exhibit various poses in daily life as they bend, sit down, touch or interact with each other. A robust people detector should detect humans also in these arbitrary poses. In addition, mobile robots should be able to carry out detection in a real-time manner because our environment is highly dynamic. In this study we developed a fast head and people detector which can, pose invariantly, detect people. Method depends only on depth information of point clouds taken from RGB-D sensors. As a result, it is robust against sudden light and contrast changes. The algorithm runs relying only on CPU, which makes it applicable to mobile robots with low computational resources.