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A 2-dimensional ACO-based path planner for off-line robot path planning

机译:基于二维ACO的路径规划器,用于离线机器人路径规划

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摘要

Wireless sensor networks are usually deployed in scenarios that are too hostile for human personnel to perform maintenance tasks. Wireless sensor nodes usually exchange information in a multi-hop manner. Connectivity is crucial to the performance of a wireless sensor network. In case a network is partitioned due to node failures, it is possible to re-connect the fragments by setting up bridges using mobile platforms. Given the landscape of a terrain, the mobile platforms should be able reach the target position using a desirable path. In this paper, an off-line robot path planner is proposed to find desirable paths between arbitrary points in a given terrain. The proposed path planner is based on ACO algorithms. Unlike ordinary ACO algorithms, the proposed path planner provides its artificial ants with extra flexibility in making routing decisions. Simulation results show that such enhancement can greatly improve the qualities of the paths obtained. Performances of the proposed path planner can be further optimized by fine-tuning its parameters.
机译:无线传感器网络通常部署在对人类人员过于敌视而无法执行维护任务的场景中。无线传感器节点通常以多跳方式交换信息。连接性对于无线传感器网络的性能至关重要。如果由于节点故障对网络进行了分区,则可以通过使用移动平台设置网桥来重新连接片段。在给定地形的情况下,移动平台应能够使用理想路径到达目标位置。在本文中,提出了一种离线机器人路径规划器,以查找给定地形中任意点之间的理想路径。提出的路径规划器基于ACO算法。与普通的ACO算法不同,拟议的路径规划器在制定路由决策时为其人工蚂蚁提供了额外的灵活性。仿真结果表明,这种增强可以大大提高获得的路径的质量。拟议的路径规划器的性能可以通过微调其参数来进一步优化。

著录项

  • 作者

    Ganganath, N; Cheng, CT;

  • 作者单位
  • 年度 2013
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
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