Anytime Coevolution of Form and Function

Abstract

This paper describes an approach to continuous coevolution of form (the morphology) and function (the control behavior) for autonomous vehicles. This study focuses on coevolution of the characteristics such as beam width and range of individual sensors in the sensor suite, and the reactive strategies for collision-free navigation for an autonomous micro air vehicle. The results of the evolution of the system in a fixed simulation model were compared to case-based anytime learning (also called continuous and embedded learning) where the simulation model was updated over time to better match changes in the environment.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA480609

Entities

People

  • Alan C. Schultz
  • Magdalena D. Bugajska

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Adaptive Systems
  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Autonomous Vehicles
  • Climate Change
  • Collisions
  • Computations
  • Computer Science
  • Environment
  • Learning
  • Micro Air Vehicles
  • Navigation
  • Personal Information Managers
  • Simulations
  • Three Dimensional
  • Vehicles

Readers

  • Artificial Intelligence
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • Autonomy