3D Pathfinding and Collision Avoidance Using Uneven Search-space Quantization and Visual Cone Search
Diptangshu Pandit

TL;DR
This paper introduces a novel 3D pathfinding algorithm that optimizes search space unevenly and employs visual cone search, enabling efficient real-time navigation without grid division, suitable for game development.
Contribution
It presents a dynamic search space optimization method for 3D pathfinding and a simplified algorithm using ray-casting, advancing real-time navigation in 3D game environments.
Findings
Reduces search nodes significantly compared to uniform grids
Enables real-time pathfinding without 3D grid division
Demonstrates effectiveness through Unreal Engine simulations
Abstract
Pathfinding is a very popular area in computer game development. While two-dimensional (2D) pathfinding is widely applied in most of the popular game engines, little implementation of real three-dimensional (3D) pathfinding can be found. This research presents a dynamic search space optimization algorithm which can be applied to tessellate 3D search space unevenly, significantly reducing the total number of resulting nodes. The algorithm can be used with popular pathfinding algorithms in 3D game engines. Furthermore, a simplified standalone 3D pathfinding algorithm is proposed in this paper. The proposed algorithm relies on ray-casting or line vision to generate a feasible path during runtime without requiring division of the search space into a 3D grid. Both of the proposed algorithms are simulated on Unreal Engine to show innerworkings and resultant path comparison with A*. The…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsArtificial Intelligence in Games · Digital Games and Media · Video Analysis and Summarization
