Motion Planning and Synthesis of Human-Like Characters in Constrained Environments

Authors:
Liangjun Zhang;Jia Pan;Dinesh Manocha
Affiliations:
Dept. of Computer Science, University of North Carolina at Chapel Hill,;Dept. of Computer Science, University of North Carolina at Chapel Hill,;Dept. of Computer Science, University of North Carolina at Chapel Hill,
Venue:
MIG '09 Proceedings of the 2nd International Workshop on Motion in Games
Year:
2009

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Abstract

We give an overview of our recent work on generating naturally-looking human motion in constrained environments with multiple obstacles. This includes a whole-body motion planning algorithm for high DOF human-like characters. The planning problem is decomposed into a sequence of low dimensional sub-problems. We use a constrained coordination scheme to solve the sub-problems in an incremental manner and a local path refinement algorithm to compute collision-free paths in tight spaces and satisfy the statically stable constraint on CoM. We also present a hybrid algorithm to generate plausible motion by combing the motion computed by our planner with mocap data. We demonstrate the performance of our algorithm on a 40 DOF human-like character and generate efficient motion strategies for object placement, bending, walking, and lifting in complex environments.