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

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.