Structure fires are responsible for the majority of fire-related deaths
nationwide. In order to assist with the rapid evacuation of trapped people,
this paper proposes the use of a system that determines optimal search paths
for firefighters and exit paths for civilians in real time based on
environmental measurements. Through the use of a LiDAR mapping system evaluated
and verified by a trust range derived from sonar and smoke concentration data,
a proposed solution to low visibility mapping is tested. These independent
point clouds are then used to create distinct maps, which are merged through
the use of a RANSAC based alignment methodology and simplified into a
visibility graph. Temperature and humidity data are then used to label each
node with a danger score, creating an environment tensor. After demonstrating
how a Linear Function Approximation based Natural Policy Gradient RL
methodology outperforms more complex competitors with respect to robustness and
speed, this paper outlines two systems (savior and refugee) that process the
environment tensor to create safe rescue and escape routes, respectively.

通过使用激光雷达测绘系统，结合声纳和烟雾浓度数据，本文提出了一种实时确定消防人员搜索路径和平民撤离路径的系统，通过对独立点云数据的合并和简化，以及根据温湿度数据为每个节点标注危险分数，建立了一个环境张量，并通过线性函数逼近基于自然政策梯度强化学习方法，证明其在鲁棒性和速度方面优于更复杂的竞争方法，最后，提出了两个系统（救助者和难民）用于处理环境张量，分别创建安全救援和逃生路线。