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Racing Vehicle Control Using Insect Intelligence

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Racing Vehicle Control Using Insect Intelligence. Ivar Mossin & Ralph Meijer. Insect Intelligence ... Seldom used to directly control game entity. Restricted ... – PowerPoint PPT presentation

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Title: Racing Vehicle Control Using Insect Intelligence


1
Racing Vehicle Control Using Insect Intelligence
  • Ivar Mossin Ralph Meijer

2
Insect Intelligence
  • What is it?
  • Artificial Life Methods
  • Hierarchical Decision-making
  • Simple toolset of sensors, functions and
    activators

3
Insect Intelligence
  • Seldom used to directly control game entity
  • Restricted minimal representation
  • Physical model what the agent thinks
  • A combination of three things
  • Exteroception
  • Proprioception
  • Body sense

4
Insect Intelligence
  • Implementation
  • On each iteration
  • Updates all agents with sensor inputs
  • Each agent express its behavior
  • Behavior of the agent is read from output
  • Game updates physical agent-state

5
Insect Intelligence
  • Traditional closed-loop feedback system
  • Measurement compared with setpoint
  • Decides action to compensate for error
  • Insect Intelligence approach
  • Sensor-inputs compared with agent wants
  • Decides action to reach goal

6
Insect Intelligence
  • What is it good for?
  • Many simple tasks instead of one complex
  • Easier to understand, design and implement
  • Performs complex tasks when put together
  • Self-calibrating
  • Differentiable / nondifferentiable operations

7
Insect Intelligence
  • Integrating with a Game Engine
  • Does not need direct access to the games physics
    engine
  • Can simulate user-input

8
An Insect Intelligent Inspired Application
  • The Racing game Downforce

9
The Fundamental Data Abstraction
  • Track Space
  • Transforms the position of the car
  • Removal of corners
  • Representing the track as a long strip
  • Width 1.0
  • (Infinite) Length
  • fWidthPos
  • fLengthPos

10
Implementation Track Space Transform
  • Array of Track lines
  • Left Edges, Right Edges, and Race lines
  • fLengthPos value
  • The whole number component
  • The fractional component

11
Implementation Track Space Transform
12
Downforce AI system overview
  • Layered approach derived from Brooks
    Subsumption Architecture
  • Downforce AI is primarily reactive
  • Hierarchically organized layers
  • Responsible for specific tasks

13
Downforce AI system overview
14
Downforce AI system overview
  • Behaviours
  • Layers are composed into sub-tasks or behaviours
  • Interaction between layers
  • Override the output
  • Affect the internal state of another layer
  • Change another layers input

15
Path Following Layer
  • Responsible for following a path at maximized
    speed
  • Steering control behaviour
  • Speed regulation behaviour

16
Tactical Racing Layer
  • Responsible for making tactical decisions
  • Choose most appropriate road position
  • Generating a new racing line
  • Collision Avoidance speed control

17
Fine grain avoidance layer
  • Responsible to deal with potential collision
    situations
  • Race priority behaviour
  • Collision avoidance behaviour

18
Driving Assist Layer
  • Responsible for control
  • Maximum traction under acceleration
  • Preventing the brakes from locking

19
Conclusions of the AI application Downforce
  • Its behavioural functionality is modular,
    extensible, and scalable
  • Complexity is reduced through decentralization

20
References
  • Biasillo, Gari, Racing AI Logic. AI Game
    Programming Wisdom, Electronic Arts Canada, 2002.
  • Darby, Alex, Racing Vehicle Control using Insect
    Intelligence. AI Game Programming Wisdom 2,
    FreeStyleGames Ltd., 2003.
  • Porcino, Nick, Insect AI 2 Implementation
    Strategies. AI Game Programming Wisdom 3,
    LucasArts, a Lucasfilm Company, 2006

21
  • Questions
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