IEEE Trans Cybern. 2017 Apr;47(4):974-983. doi: 10.1109/TCYB.2016.2535153. Epub 2016 Mar 15.
Intending to mimic the operating mechanism of biological neural systems, a self organizing map-based approach to task assignment of a swarm of robots in 3-D dynamic environments is proposed in this paper. This approach integrates the advantages and characteristics of biological neural systems. It is capable of dynamically planning the paths of a swarm of robots in 3-D environments under uncertain situations, such as when some robots are presented in or broken down or when more than one robot is needed for some special task locations. A Bezier path optimizing algorithm and a parameter adjusting algorithm are integrated in this paper. It is capable of reducing the complexity of the robot navigation control and limiting the number of convergence iterations. The simulation results with different environments demonstrate the effectiveness of the proposed approach.
本文提出了一种基于自组织映射的方法，旨在模拟生物神经网络系统的运行机制，以实现 3D 动态环境中机器人群体的任务分配。该方法集成了生物神经网络系统的优势和特点，能够在不确定情况下动态规划机器人在 3D 环境中的路径，例如当一些机器人出现或损坏时，或者当某些特殊任务位置需要多台机器人时。本文还集成了贝塞尔路径优化算法和参数调整算法，能够降低机器人导航控制的复杂性并限制收敛迭代次数。不同环境下的仿真结果证明了该方法的有效性。
