Multi-Contact Interaction Force Sensing from Whole-Body Motion Capture

Tu-Hoa Pham, Stéphane Caron and Abderrahmane Kheddar. IEEE Transactions on Industrial Informatics. Submitted November 2016. Published October 2017.


We present a novel technique that unobtrusively estimates forces exerted by human participants in multi-contact interaction with rigid environments. Our method uses motion capture only, thus circumventing the need to setup cumbersome force transducers at all potential contacts between the human body and the environment. This problem is particularly challenging, as the knowledge of a given motion only characterizes the resultant force, which can generally be caused by an infinity of force distributions over individual contacts. We collect and release a large-scale dataset on how humans instinctively regulate interaction forces on diverse multi-contact tasks and motions. The force estimation framework we propose leverages physics-based optimization and neural networks to reconstruct force distributions that are physically realistic and compatible with real interaction force patterns. We show the effectiveness of our approach on various locomotion and multi-contact scenarios.


  title = {Multi-Contact Interaction Force Sensing from Whole-Body Motion Capture},
  author = {Pham, Tu-Hoa and Caron, St{\'e}phane and Kheddar, Abderrahmane},
  journal = {IEEE Transactions on Industrial Informatics},
  year = {2017},
  doi = {10.1109/TII.2017.2760912},
  publisher = {IEEE},


There are no comments yet. Feel free to leave a reply using the form below.

Post a comment

You can use Markdown with $\LaTeX$ formulas in your comment.

You agree to the publication of your comment on this page under the CC BY 4.0 license.

Your email address will not be published.