Neuroevolution of Actively Controlled Virtual Characters

Master's thesis Information- and communication technology IKT590 - University of Agder 2017Physics-based character animation offer an attractive alternative to traditional animation techniques, however, physics-based approaches often struggle to incorporate active user control of these characters. This thesis suggests a different approach to the problem of actively controlled virtual characters. The proposed solution takes a neuroevolutionary approach, using HyperNEAT to evolve neural controllers for a simulated eight-legged character, a previously untested character morphology for this algorithm. Using these controllers this thesis aims to evaluate the robustness and responsiveness of a control strategy that changes between them based on simulated user input. The results show that HyperNEAT is quite capable of evolving long walking controllers for this character, but also suggests a need for further refinement when operated in tandem

Simple Data-Driven Control for Simulated Bipeds

We present a framework for controlling physics-based bipeds in a simulated environment, based on a variety of reference motions. Unlike existing methods for control based on reference motions, our framework does not require preprocessing of the reference motion, nor does it rely on inverse dynamics or on-line optimization methods for torque computation. It consists of three components: Proportional-Derivative Control to mimic motion characteristics, a specific form of Jacobian Transpose Control for balance control, and Covariance Matrix Adaption for off-line parameter optimization, based on a novel high-level reward function. The framework can easily be implemented using common off-the-shelf physics engines, and generates simulations at approximately 4 realtime on a single core of a modern PC. Our framework advances the state-of-the-art by demonstrating motions of a diversity and dynamic nature previously unseen in comparable methods, including squatting, bowing, kicking, and dancing motions. We also demonstrate its ability to withstand external perturbations and adapt to changes in character morphology