![[2602.21174] Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2602.21174] Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids
Summary
This paper presents an efficient hierarchical approach for any-angle path planning on multi-resolution 3D grids, addressing scalability issues in large-scale environments.
Why It Matters
The research is significant as it enhances path planning methods in robotics by combining optimality and computational efficiency, which is crucial for applications in complex environments. The open-source framework allows for broader community engagement and development.
Key Takeaways
- Introduces a novel method for any-angle path planning that utilizes multi-resolution representations.
- Demonstrates improved solution quality and speed compared to traditional sampling-based methods.
- Addresses scalability challenges in path planning for large, complex environments.
- Offers an open-source framework to facilitate further research and application in the robotics community.
- Highlights the importance of optimality and completeness in path planning algorithms.
Computer Science > Robotics arXiv:2602.21174 (cs) [Submitted on 24 Feb 2026] Title:Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids Authors:Victor Reijgwart, Cesar Cadena, Roland Siegwart, Lionel Ott View a PDF of the paper titled Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids, by Victor Reijgwart and 2 other authors View PDF HTML (experimental) Abstract:Hierarchical, multi-resolution volumetric mapping approaches are widely used to represent large and complex environments as they can efficiently capture their occupancy and connectivity information. Yet widely used path planning methods such as sampling and trajectory optimization do not exploit this explicit connectivity information, and search-based methods such as A* suffer from scalability issues in large-scale high-resolution maps. In many applications, Euclidean shortest paths form the underpinning of the navigation system. For such applications, any-angle planning methods, which find optimal paths by connecting corners of obstacles with straight-line segments, provide a simple and efficient solution. In this paper, we present a method that has the optimality and completeness properties of any-angle planners while overcoming computational tractability issues common to search-based methods by exploiting multi-resolution representations. Extensive experiments on real and synthetic environments demonstrate the proposed approach's solution quality and speed, outperf...