Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
Autonomous Robots
Distributed, Physics-Based Control of Swarms of Vehicles
Autonomous Robots
Self-Organizing and Scalable Shape Formation for a Swarm of Pico Satellites
AHS '08 Proceedings of the 2008 NASA/ESA Conference on Adaptive Hardware and Systems
Lower bounds for asynchronous consensus
Future directions in distributed computing
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We present a distributed control strategy that lets a swarm of satellites autonomously form a lattice in orbit around a planet. The system, based on the artificial potential field approach, proposes a novel way to split the artificial field in two main terms: a global artificial field that gathers the satellites around a predefined meeting point, and a local term that allows a satellite to place itself in the correct position relative to its closest neighbors. We apply the method to the problem of forming a two dimensional hexagonal lattice, using the well-known Lennard-Jones potential as local artificial field. The control parameters have been obtained with a genetic algorithm to maximize the precision of the formed lattice. The precision does not depend on the number of satellites and convergence is achieved from all initial distributions of the satellites.