虚拟绳系搜索:一个自约束搜索算法的群体在开放的海洋

S. Tolba, R. Ammar
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引用次数: 1

摘要

与地面机器人群相比,水下机器人群的操作条件更具挑战性。其中一个主要的限制是海洋环境的浩瀚,这大大增加了失去群体成员的可能性。虽然群体可以容忍损失,但如果在设计群体行为时不小心,它们可能会导致任务的彻底失败。因此,这种系统的另一个设计因素是群体的空间约束性。虚拟系绳搜索(VTS)的开发就是为了解决这个问题。机器人使用连接在落点上的虚拟缆绳以及航位推算来保持与该地点的最大半径距离。将先前开发的约束螺旋群集算法(CSF)、机器人粒子群优化算法(R-PSO)和简单扫描算法(SSW)与VTS进行了比较,并强调了每种算法的优缺点。VTS在全方向性和防丢失方面具有优越的性能,但收敛速度相对较慢,但有保证。
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Virtual Tether Search: A self-constraining search algorithm for swarms in an open ocean
Underwater robotic swarms have more challenging operating conditions when compared to their ground counterparts. One such major limitation is vastness of the oceanic environment, which significantly increases the possibility of losing swarm members. Although swarms can tolerate losses, if care is not taken in the design of swarm-level behaviors, they can cause a complete failure of the mission. An additional design factor for such systems is, therefore, the spatial constrained-ness of the swarm. Virtual Tether Search (VTS) has been developed to address this concern. Robots use a virtual tether attached to the drop-off location along with dead-reckoning to stay within a maximum-radius distance from that location. Constrained Spiral Flocking (CSF), a previously developed algorithm, Robotic Particle Swarm Optimization (R-PSO), and Simple Sweeping (SSW) are compared to VTS and pros and cons of each algorithm are highlighted. VTS is shown to have a superior behavior in terms of omni-directionality and loss-prevention at the expense of relatively slow, but guaranteed convergence.
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