Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Adaptive algorithms and stochastic approximations
Adaptive algorithms and stochastic approximations
IEEE Computational Intelligence Magazine
Autonomous Self-Assembly in Swarm-Bots
IEEE Transactions on Robotics
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Stability analysis of social foraging swarms
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Cooperative behavior of nano-robots as an analogous of the quantum harmonic oscillator
Annals of Mathematics and Artificial Intelligence
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Two distributed stochastic search algorithms are proposed for motion planning of multi-robot systems: (i) distributed gradient, (ii) swarm intelligence theory. Distributed gradient consists of multiple stochastic search algorithms that start from different points in the solutions space and interact with each other while moving toward the goal position. Swarm intelligence theory is a derivative-free approach to the problem of multi-robot cooperation which works by searching iteratively in regions defined by each robot's best previous move and the best previous move of its neighbors. The performance of both approaches is evaluated through simulation tests.