Glen Berseth

Randomized, continuous footstep action space.

Geometric validation to ensure valid configuration.

With this work we build upon prevous work to inductavely design a robust footsteps-based steering algorithm. The steering algorithm uses an A* algorithm to generate least cost footstep plans between goals while avoiding dynamic collisions.

Abstract

A number of recent agent-based steering methods abandon the standard particle abstraction of an agent's locomotion abilities, and employ more complex models from timed footsteps to physics-based controllers. These models often provide the action space of an optimal search method that plans a sequence of steering actions for each agent that minimize a performance criterion. The transition from particle based models to more complex ones is not straightforward and gives rise to a number of technical challenges. For example, a particle representation is constant, symmetric and convex, while a footstep model maybe non-convex and dynamic. In this paper, we discuss our recent experience with a few of specific issues, and how we addressed them in the context of space-time footstep planning for steering virtual humans.

Bibtex

You can find the paper describing the project here
You can the presentation for the work here

This video demonstrates some of the example results of robust footsteps algorithm.

Recieved CASA2015 Best Short Paper Award

Photo - From Left to Right: Glen Berseth and Prof Jian Jun Zhang