# Enhanced UAV Path Planning Using the Tangent Intersection Guidance (TIG) Algorithm

arXiv: https://arxiv.org/abs/2508.18967 · HTML: https://mlsanity.com/paper/2508.18967/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 61 references that are in the map.
- First posted on arXiv 26 Aug 2025.

## Builds on (most cited first, 4 of 4)

- [Deep Reinforcement Learning: An Overview](https://mlsanity.com/paper/1701.07274/) (2017)
- [Joint Ground and Aerial Package Delivery Services: A Stochastic Optimization Approach](https://mlsanity.com/paper/1808.04617/) (2018)
- [An Autonomous Path Planning Method for Unmanned Aerial Vehicle based on A Tangent Intersection and Target Guidance Strategy](https://mlsanity.com/paper/2006.04103/) (2020)
- [Remote UAV Online Path Planning via Neural Network Based Opportunistic Control](https://mlsanity.com/paper/1910.04969/) (2019)

## Built on by (most cited first, 1 of 1)

- [Convex-Neural RRT*: Fast and Reliable Learning-Guided Sampling for High-Quality Robot Path Planning](https://mlsanity.com/paper/2605.25006/) (2026)

## Abstract (arXiv)

Efficient and safe navigation of Unmanned Aerial Vehicles (UAVs) is critical for various applications, including combat support, package delivery and Search and Rescue Operations. This paper introduces the Tangent Intersection Guidance (TIG) algorithm, an advanced approach for UAV path planning in both static and dynamic environments. The algorithm uses the elliptic tangent intersection method to generate feasible paths. It generates two sub-paths for each threat, selects the optimal route based on a heuristic rule, and iteratively refines the path until the target is reached. Considering the UAV kinematic and dynamic constraints, a modified smoothing technique based on quadratic B'ezier curves is adopted to generate a smooth and efficient route. Experimental results show that the TIG algorithm can generate the shortest path in less time, starting from 0.01 seconds, with fewer turning angles compared to A*, PRM, RRT*, Tangent Graph, and Static APPATT algorithms in static environments. Furthermore, in completely unknown and partially known environments, TIG demonstrates efficient real-time path planning capabilities for collision avoidance, outperforming APF and Dynamic APPATT algorithms.