Abstract Locomotion Synthesis Methods for Humanoid Characters

This thesis introduces locomotion synthesis methods for humanoid characters. Motion synthesis is an under-constrained problem that requires additional constraints beyond user inputs. Two main approaches to introducing additional constraints are physics-based and data-driven. Despite significant progress in the past 20 years, major difficulties still exist for both approaches. In general, building animation systems that are flexible to user requirements while keeping the synthesized motions plausible remain a challenging task. The methods introduced in this thesis, presented in two-parts, aim to allow animation systems to be more flexible to user demands without radically violating constraints that are important for maintaining plausibility. In the first part of the thesis, we address an important subproblem in physics-based animation — controller synthesis for humanoid characters. We describe a method for optimizing the parameters of a physics-based controller for full-body, 3D walking. The objective function includes terms for power minimization, angular momentum minimiza-tion, and minimal head motion, among others. Together these terms produce a number of important features of natural walking, including active toe-off, near-passive knee swing