Proceedings: GI 2005

Controllable real-time locomotion using mobility maps

Madhusudhanan Srinivasan , Ronald Metoyer , Eric Mortensen

Proceedings of Graphics Interface 2005: Victoria, British Columbia, Canada, 9 - 11 May 2005, 51-59

DOI 10.20380/GI2005.07

  • Bibtex

    @inproceedings{Srinivasan:2005:10.20380/GI2005.07,
    author = {Srinivasan, Madhusudhanan and Metoyer, Ronald and Mortensen, Eric},
    title = {Controllable real-time locomotion using mobility maps},
    booktitle = {Proceedings of Graphics Interface 2005},
    series = {GI 2005},
    year = {2005},
    issn = {0713-5424},
    isbn = {1-56881-265-5},
    location = {Victoria, British Columbia, Canada},
    pages = {51--59},
    numpages = {9},
    doi = {10.20380/GI2005.07},
    publisher = {Canadian Human-Computer Communications Society},
    address = {School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada},
    }

Abstract

Graph-based approaches for sequencing motion capture data have produced some of the most realistic and controllable character motion to date. Most previous graph-based approaches have employed a run-time global search to find paths through the motion graph that meet user-defined constraints such as a desired locomotion path. Such searches do not scale well to large numbers of characters. In this paper, we describe a locomotion approach that benefits from the realism of graph-based approaches while maintaining basic user control and scaling well to large numbers of characters. Our approach is based on precomputing multiple least cost sequences from every state in a state-action graph. We store these precomputed sequences in a data structure called a mobility map and perform a local search of this map at run-time to generate motion sequences in real time that achieve user constraints in a natural manner. We demonstrate the quality of the motion through various example locomotion tasks including target tracking and collision avoidance. We demonstrate scalability by animating crowds of up to 150 rendered articulated walking characters at real-time rates.