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Onboard robust person detection and tracking for domestic service robots


Conference Paper


Domestic assistance for the elderly and impaired people is one of the biggest upcoming challenges of our society. Consequently, in-home care through domestic service robots is identified as one of the most important application area of robotics research. Assistive tasks may range from visitor reception at the door to catering for owner's small daily necessities within a house. Since most of these tasks require the robot to interact directly with humans, a predominant robot functionality is to detect and track humans in real time: either the owner of the robot or visitors at home or both. In this article we present a robust method for such a functionality that combines depth-based segmentation and visual detection. The robustness of our method lies in its capability to not only identify partially occluded humans (e.g., with only torso visible) but also to do so in varying lighting conditions. We thoroughly validate our method through extensive experiments on real robot datasets and comparisons with the ground truth. The datasets were collected on a home-like environment set up within the context of RoboCup@Home and RoCKIn@Home competitions.

Author(s): Sanz, D and Ahmad, A and Lima, P
Book Title: Robot 2015: Second Iberian Robotics Conference
Pages: 547-559
Year: 2015
Series: Advances in Intelligent Systems and Computing ; 418
Publisher: Springer

Department(s): Perceiving Systems
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1007/978-3-319-27149-1_42
Event Name: Second Iberian Robotics Conference (ROBOT’2015)
Event Place: Lisboa, Portugal

Address: Cham, Switzerland


  title = {Onboard robust person detection and tracking for domestic service robots},
  author = {Sanz, D and Ahmad, A and Lima, P},
  booktitle = {Robot 2015: Second Iberian Robotics Conference},
  pages = {547-559},
  series = {Advances in Intelligent Systems and Computing ; 418},
  publisher = {Springer},
  address = {Cham, Switzerland},
  year = {2015}