Direct visual SLAM fusing proprioception for a humanoid robot

Raluca Scona, Simona Nobili, Yvan R. Petillot, Maurice Fallon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

In this paper we investigate the application of semi-dense visual Simultaneous Localisation and Mapping (SLAM) to the humanoid robotics domain. Challenges of visual SLAM applied to humanoids include the type of dynamic motion executed by the robot, a lack of features in man-made environments and the presence of dynamics in the scene. Previous research on humanoid SLAM focused mostly on feature-based methods which result in sparse environment reconstructions. Instead, we investigate the application of a modern direct method to obtain a semi-dense visually interpretable map which can be used for collision free motion planning. We tackle the challenge of using direct visual SLAM on a humanoid by proposing a more robust pose tracking method. This is formulated as an optimisation problem over a cost function which combines information from the stereo camera and a low-drift kinematic-inertial motion prior. Extensive experimental demonstrations characterise the performance of our method using the NASA Valkyrie humanoid robot in a laboratory environment equipped with a Vicon motion capture system. Our experiments demonstrate pose tracking robustness to challenges such as sudden view change, motion blur in the image, change in illumination and tracking through sequences of featureless areas in the environment. Finally, we provide a qualitative evaluation of our stereo reconstruction against a LIDAR map.

Original languageEnglish
Title of host publication2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Pages1419-1426
Number of pages8
ISBN (Electronic)9781538626825
DOIs
Publication statusPublished - 14 Dec 2017
Event30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017 - Vancouver, Canada
Duration: 24 Sep 201728 Sep 2017

Publication series

NameIEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherIEEE
ISSN (Electronic)2153-0866

Conference

Conference30th IEEE/RSJ International Conference on Intelligent Robots and Systems 2017
Abbreviated titleIROS 2017
CountryCanada
CityVancouver
Period24/09/1728/09/17

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Scona, R., Nobili, S., Petillot, Y. R., & Fallon, M. (2017). Direct visual SLAM fusing proprioception for a humanoid robot. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 1419-1426). (IEEE/RSJ International Conference on Intelligent Robots and Systems). IEEE. https://doi.org/10.1109/IROS.2017.8205943