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. © Springer-Verlag 2009.
CITATION STYLE
Zhang, L., Pan, J., & Manocha, D. (2009). Motion planning and synthesis of human-like characters in constrained environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5884 LNCS, pp. 138–145). https://doi.org/10.1007/978-3-642-10347-6_13
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