基于多目标次优视角探索的消防行动移动算子寻找

Nils Mandischer, Marius Gürtler, Sebastian Döbler, M. Hüsing, B. Corves
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引用次数: 0

摘要

最近设计的许多搜救探索算法都是将现有的探索算法扩展到多个同时运行的智能体上。这些算法在大范围的搜索和救援行动中非常有用,但忽略了对小规模环境所需的适应性的需要。因此,本文提出了一种新的模块化多层方法,该方法将传统的次优视图探索与预定义的边界条件相结合,以实现对受害者和操作员的多目标驱动搜索。边界条件分别映射到代价映射上,并动态融合到一个公共加权矩阵中。典型的情况是最后已知的操作员姿势或火源的估计位置。探索算法比较附近兴趣点的权重,选择合适的导航目标。该方法在人类和机器人团队的消防行动中进行了评估。
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Finding Moving Operators in Firefighting Operations Based on Multi-Goal Next-Best-View Exploration
Many recently designed exploration algorithms for search and rescue are based on the expansion of existing exploration algorithms to multiple simultaneously operating agents. These algorithms are quite useful in extensive search and rescue operations but neglect the need for adaptability necessary in small scale environments. Therefore, this paper proposes a novel modular multi-layer approach, which combines conventional Next-Best-View Exploration with predefined boundary conditions to enable a multi-goal driven search for victims and operators. The boundary conditions are mapped on cost maps individually and fused dynamically in a common weighting matrix. Exemplary conditions are the last known operator pose or estimated positions of fire sources. The exploration algorithm compares nearby points of interest in regards to their weight and chooses an appropriate navigation goal. The method is evaluated for usage in context of firefighting operations with teams of humans and robots.
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