SIGGRAPH 2010 By Focus
Sampling-Based Contact-Rich Motion Control
Given a motion trajectory, this method reconstructs its control by randomized sampling. The paper demonstrates fast reconstruction for a diverse set of captured motions, including contact-rich tasks such as forward and sideways rolls. Physically plausible motion transformation and retargeting, and reference-trajectory-free idling can be done within the same framework.
Data-Driven Biped Control
A dynamic controller to physically simulate three-dimensional full-body biped locomotion. The data-driven controller uses motion capture reference data to reproduce realistic human locomotion through real-time simulation. This paper demonstrates the effectiveness of the approach through examples that allow bipeds to turn, spin, and walk while their direction is steered interactively.
Generalized Biped Walking Control
A simple control strategy for physically simulated walking that generalizes well across gait parameters, motion styles, character proportions, and a variety of skills, such as picking up objects placed at any height, pushing and pulling, stepping over obstacles, and walking with crates.
Feature-Based Locomotion Controllers
A technique for building locomotion controllers for physics-based characters in terms of high-level features. Objective terms control each feature and are combined using a strict prioritization algorithm. Using this approach, human-like qualities emerge automatically and control can be mapped onto new bipeds without modifications.