Real time whole body motion mapping for avatars and robots

Conference paper

Spanlang, B., Navarro, X., Normand, J.-M., Kishore, S., Pizarro, R. and Slater, M. 2013. Real time whole body motion mapping for avatars and robots. 19th ACM Symposium on Virtual Reality Software and Technology. Singapore 06 - 09 Oct 2013 Association for Computing Machinery (ACM). https://doi.org/10.1145/2503713.2503747
TypeConference paper
TitleReal time whole body motion mapping for avatars and robots
AuthorsSpanlang, B., Navarro, X., Normand, J.-M., Kishore, S., Pizarro, R. and Slater, M.
Abstract

We describe a system that allows for controlling different robots and avatars from a real time motion stream. The underlying problem is that motion data from tracking systems is usually represented differently to the motion data required to drive an avatar or a robot: there may be different joints, motion may be represented by absolute joint positions and rotations or by a root position, bone lengths and relative rotations in the skeletal hierarchy. Our system resolves these issues by remapping in real time the tracked motion so that the avatar or robot performs motions that are visually close to those of the tracked person. The mapping can also be reconfigured interactively at run-time. We demonstrate the effectiveness of our system by case studies in which a tracked person is embodied as an avatar in immersive virtual reality or as a robot in a remote location. We show this with a variety of tracking systems, humanoid avatars and robots.

Keywordsavatars; robots; virtual reality; motion capture
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeCreativity, Culture & Enterprise
Conference19th ACM Symposium on Virtual Reality Software and Technology
Proceedings TitleProceedings of the ACM Symposium on Virtual Reality Software and Technology
ISBN9781450323796
PublisherAssociation for Computing Machinery (ACM)
Publication dates
Online06 Oct 2013
Print06 Oct 2013
Publication process dates
Deposited30 Oct 2023
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1145/2503713.2503747
Scopus EID2-s2.0-84887148478
LanguageEnglish
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