Multi-Level Indoor Path Planning and Clearance-Based Path Optimization for Search and Rescue Operations

Abstract

In this study a multi-level path planning system is proposed for indoor search and rescue operations. Requirements for the path planning system are derived based on the operational concept of the integrated indoor navigation system. Different aspects of various path planning algorithms are assessed, and their suitability to search and rescue operations in structured indoor environments is investigated. A fivestep path planning system is proposed, which consists of map pre-processing, segment path planning, graph processing, route optimization, and path post-processing. The proposed method addresses a multi-goal path planning problem in a multi-story building in a computationally efficient way by adopting a graph-based approach while satisfying such requirements as clearance conditions in the pre-and post-processing steps. Furthermore, a multi-query approach is adopted to exploit the response time and earn flexibility with respect to environmental changes. The effectiveness of the proposed path planning system is demonstrated through numerical simulations.INDEX TERMS Path planning, indoor navigation, path optimization, linear programming, dynamic environment.

Simulation Analysis of Fire-Fighting Path Planning Based On SLAM

“…These signatures are typically formed using a bag-of-words model, where each word represents a feature in the image or map. The words in the signature are stored in a dictionary, which can be calculated by equation (1).…”

“…The current research on path planning algorithms mainly includes the improvement of traditional algorithms and the application of intelligent bionic algorithms, including the A * algorithm, Dijkstra algorithm,genetic algorithm,ant colony algorithm, artificial potential field algorithm, etc. Among them, the most popular progamme for many applications are A* and a rapidly exploring random tree (RRT) [1] , and both of them are applicable in static environments. The A* algorithm locates the path with the lowest cost in static settings, which has some useful characteristics, such as intgrity, optimality, and optimal efficiency.…”