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.
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Zhang, L., Pan, J., Manocha, D. (2009). Motion Planning and Synthesis of Human-Like Characters in Constrained Environments. In: Egges, A., Geraerts, R., Overmars, M. (eds) Motion in Games. MIG 2009. Lecture Notes in Computer Science, vol 5884. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10347-6_13
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DOI: https://doi.org/10.1007/978-3-642-10347-6_13
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