Co-Evolution of Form and Function in the Design of Autonomous Agents: Micro Air Vehicle Project
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Summary
The evolution of an optimal minimum sensor suite and reactive strategies for navigation and collision avoidance for the simulated MAV is described.
- Type
- article
- Published
- 2000-07-08
- Cited by
- 35
- References
- 17
- OpenAlex
- https://openalex.org/W42070915
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17040593
Keywords
Collision avoidance, Suite, Genetic algorithm, Function (biology), Computer science
References
- Computer Evolution of Buildable Objects
- Using a Genetic Algorithm to Learn Strategies for Collision Avoidance and Local Navigation.
- How to Evolve Autonomous Robots: Different Approaches in Evolutionary Robotics
- A framework for sensor evolution in a population of Braitenberg vehicle-like agents (poster)
- Evolving the morphology of a compound eye on a robot
- Evolving robot morphology
- Evolving 3D Morphology and Behavior by Competition
- Evolution of homing navigation in a real mobile robot
- A hybrid GP/GA approach for co-evolving controllers and robot bodies to achieve fitness-specified tasks
- Learning to fly.
- Issues in evolutionary robotics
- Two Applications of Genetic Algorithms to Component Design
- The User''s Guide to SAMUEL, Version 1.3
- On sensor evolution in robotics
- Evolving and Breeding Robots
Cited by
- Using coevolution in complex domains
- Towards Evolution of Collective Sensory Systems for Intelligent Vehicles
- Evolution of Control Programs for a Swarm of Autonomous Unmanned Aerial Vehicles
- Multi-agent simulation for assessing massive sensor deployment
- Strategies for multi-asset surveillance
- EVOLVING ENGINEERING DESIGN TRADE-OFFS
- Evolution of Sensor Suites for Complex Environments
- The evolved radio and its implications for modelling the evolution of novel sensors
- Nested Reconfigurable Robots: Theory, Design, and Realization
- Deriving minimal sensory configurations for evolved cooperative robot teams
- Anytime coevolution of form and function
- Multi-Agent Simulations (MAS) for Assessing Massive Sensor Coverage and Deployment
- Challenges and Opportunities of Evolutionary Robotics
- Design and realization of the biomimetic predator-prey vision based on a self-reconfigurable robot
- Assessing Quality of Evolved Agent Controllers for Collective Gathering
- Continuous and embedded learning in autonomous vehicles: adapting to sensor failures
- Hinged-Tetro: A self-reconfigurable module for nested reconfiguration
- Toward evolved flight
- Designing teams of unattended ground sensors using genetic algorithms
- Neuro-Evolution for Emergent Specialization in Collective Behavior Systems
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