Wednesday, December 28, 2011

An Egocentric Motion Management System - article excerpt from Game Engine Gems 2

Google Books has provided a generous preview of my chapter from Game Engine Gems 2 describing a character movement solution - aspects of which I used in World of Zoo (PC & Wii). The character movement solution was also used in several demos - including a prototype of a non-zoo type game. The chapter contains a detailed write-up of how how to integrate the character movement system with a behavioral model that conveys perceived intent (section 19.9 A Single Agent Behavioral Response Algorithm and Example). The link to the article is below - enjoy!

An Egocentric Motion Management System Summary

The egocentric motion management system (ECMMS) is both a model for agent movement and an application of a behavioral theory. Any game that features agents (e.g., animals, soldiers, or tanks) that move around in a 3D scene has a need for an agent movement solution. A typical movement solution provides mechanisms that allow for an agent to move through a scene, avoiding geometry, all the while executing some sort of behavior. This article discusses not only how focusing on the agent drives the immediate interactions with the environment but also, more importantly, that by gathering some information about the environment during locomotion, we gain the ability to generate spatial semantics for use by the agent’s behavior system. Portions of the ECMMS were used in a cross-platform game entitled World of Zoo (WOZ). WOZ is an animal simulator that requires various zoo animals to move through their environments in an incredibly compelling manner while the  players constantly alter the environment. So the proving ground for this system was in an environment that could be changed around the agents at any particular moment. In addition to detailing ECMMS I also discuss how to build a unified behavioral model that utilizes technology from all three of my character movement articles.

An Egocentric Motion Management System - Theory and an Implementation

Tuesday, December 13, 2011

Qualitative Improvements of Biasing a Routes Starting Position

In this note I'll be discussing how biasing an entities starting position before providing it to the pathfinder, can improve the qualitative behavior of your game's characters. This technique was used on a multi-platform game [Ramsey 2009a].

Generating a route to destination can be parametrized in many ways, but one of the most fundamental parameters has a trickle down effect attune to an avalanche with observable repercussions on an entities motion - if selected incorrectly.

What I'm suggesting is that the start position provided to the path finder is one of the most important parameters to get correct. It almost seems intuitive to suggest that the starting point is "where your at." Well, maybe not so - we need to think temporally. Consider not only our thoughts, but our movement - it's always changing, adapting and what's appropriate at this moment in time is not necessarily appropriate 5 seconds from now, probably not even one second in the future. This applies to selecting a starting position for our animating penguin. We are more interested where it'll be rather then where it's at currently.

The picture below illustrates a simple environment where we have a penguin that wants to move from position A to position B. A typical pathfinder would be supplied with the penguins current position as the start position, and position B as the end point. The problem with this seemingly correct solution is that it fails to factor in any forward momentum of the penguin. Whether the forward momentum is implicit in the animation driving the penguin or an associated movement rate of a simple sprite where the penguin is at (t) is not where it'll be at (t+1).

The penguins directional vector is represented by the light blue line, the pink segments is the path returned if the penguins current position is used as the starting point, and the green segments is the route when we factor in not only the penguins directional vector, but also it's velocity. The yellow bidirectional connections is the graph representation of the navigation mesh.

Depending on how fast the penguin is moving, we bias the start position of the penguin farther and farther away. A simple technique is to attain the penguins heading and magnitude of translation over one frame (t). And then using a standard unit of measurement (r) - I used the diameter of the penguin, you multiply (r*t) = (s). I also experimented with the radius and this worked as well for animals that didn't translate too fast. (s) then becomes a scale that we can apply to the penguins directional vector, with a resulting point in the environment that serves as the starting point for your path finding algorithm. Straightforward and it allows for the continuation of the penguins motion with out any jarring hitches caused by the pathfinder (I had coded up a modified version of A-Star that supported our modeling methods) .

This technique is not only useful in this directed graph representation, but also on typical grids and navigation meshes. I hope you find it useful as using this technique had a qualitatively positive impact on the movement of the animals in World of Zoo.

[Gibson 1986] James J. Gibson. The Ecological Approach to Visual Perception. Hillsdale,
NJ: Lawrence Erlbaum Associates, 1986.

[Ramsey 2009a] Michael Ramsey. “A Unified Spatial Representation for Navigation
Systems.” Proceedings of The Fifth AAAI Artificial Intelligence and Interactive
Digital Entertainment Conference, 2009, pp. 119–122.

[Ramsey 2009b] Michael Ramsey. “A Practical Spatial Architecture for Animal and
Agent Navigation.” Game Programming Gems 8, edited by Adam Lake. Boston:
Charles River Media, 2010.

[Ramsey 2009c] Michael Ramsey. “An Egocentric Motion Management System.” Game Engine
Gems 2, edited by Eric Lengyel. Natick: A.K. Peters, 2011.

Further Reading
1. “On the Nature of Things” Lucretius, translated by Ronald Melville is wonderful book expounding the atomic theory first presented by Epicurus. Book I covers the two principles of beingness: that nothing ever came from nothing and that nothing ever returns to nothing. Book 2 discusses the principles of continual motion and how collisions shape the free will. Book 3 covers the nature of the mind, while Book 4 explains the nature of vision, hearing, taste, smell and how aspects of the environment enter the mind. Book 5 and 6 wrap covering mortality and environmental effects.

Friday, December 02, 2011

Noumena Philosophical Canon

While the last post attempted to cover the more concrete canon, this post will list the books that comprise my Noumena philosophical canon. Every project needs an underlying set of principles that help guide the development of not only the final product, but arguably the process in which these systems were built. These books represent some of the core books that provided ideas that contributed to Noumena's process.

1.  The Complete Works of Aristotle, ed. Jonathan Barnes
2.  The Human Touch, Michael Fray
3.  Michel De Montaigne The Complete Works, Translated by Donald Frame
4.  The Phenomenom of Life, Alexander
5.  On the Nature of Things, Lucretius
6.  Being and Time, Heidegger
7.  The World of Perception, Merleau Ponty
8.  Experience and Prediction, Hans Reichenbach
9.  The Phenomenology of Perception, Merlau Ponty
10. The Origins of Knowledge and Imagination, Jacob Bronowski

Noumena Canon

It's been a while since I posted, so here are a few of the books that I consider canon for the development of Noumena. There are literally hundreds of other books that have influenced Noumena in some form or another (I actually posted several years ago an initial list of some of the books) but these few here are the pillars on which a number of my ideas are based upon.

1.  The Philosophy of Animal Minds, ed. Robert Lutz
2.  Animal Cognition, Clive Wynne
3.  Mental Leaps, Keith Holyoak and Paul Thagard
4.  Mindreading Animals, Robert Lutz
5.  Incomplete Nature, Terrence Deacon
6.  Creating a Memory of Causal Relationships, Michael Pazzani
7.  Who Needs Emotions?, ed Jean-Marc Fellous and Michael Arbib
8.  Behavior: The Control of Perception. William T. Powers
9.  General System Theory. Ludwig von Bertalanffy
10. The Principles of Psychology, Volumes 1 & 2, William James.

Hopefully in the not too distant future, I'll be posting an outline for the manuscript entitled, "Fellow Creatures: A Referential Intelligence." It's a book that covers the development of the referentially based cognitive engine, Noumena.