Fast and efficient indoor navigation: a hybrid pathfinding approach using rapidly-exploring random tree (RRT)connect and Dijkstra’s algorithm

Abstract

This article introduces a hybrid approach to enhance indoor pathfinding and navigation within complex multistory environments by integrating rapidly-exploring random tree (RRT)-Connect and Dijkstra’s algorithm. We propose a novel solution leveraging the strengths of RRT-connect for rapid path generation, combined with Dijkstra’s algorithm for refining and optimizing the final route. Our method leverages the rapid exploration of RRT-Connect while refining paths using Dijkstra’s algorithm, resulting in fewer nodes explored compared to Lazy Theta* while maintaining efficiency. Experimental results demonstrate that our hybrid approach significantly reduces computational overhead, with RRT-Connect exploring approximately 1,750 nodes-outperforming RRT (2,000 nodes), RRT* (1,850 nodes), and Dijkstra (1,780 nodes). The algorithm achieves up to 50% faster execution in narrow spaces compared to traditional RRT, making it well-suited for real-time navigation. Additionally, parallel processing optimizes performance, ensuring efficient pathfinding in dynamic environments. A Next.js-based frontend visualization system further enhances usability by rendering path nodes in real time. This hybrid approach balances rapid exploration, optimal path computation, and computational efficiency, making it a robust solution for indoor navigation in large-scale and complex environments.