SEED Research & Announcements Blogs Publications Open Source Careers Contact Us Research & Announcements Blogs Publications Open Source Careers Contact Us

CoG 2023: Efficient Ground Vehicle Path Following in Game AI

This research paper was accepted for publication at the IEEE Conference on Games 2023 in Boston, USA.

Authors: Rodrigue de Schaetzen, Alessandro Sestini.

Efficient Ground Vehicle Path Following in Game AI

Read the full research paper.

This short paper presents an efficient path-following solution for ground vehicles tailored to game AI. 

Our focus is on adapting established techniques to design simple solutions with parameters that are easily tuneable for an efficient benchmark path follower. Our solution pays particular attention to computing a target speed, which uses quadratic Bezier curves to estimate the path curvature. The performance of the proposed path follower is evaluated through a variety of test scenarios in a first-person shooter game, demonstrating its effectiveness and robustness in handling different types of paths and vehicles. 

We achieved a 70% decrease in the total number of stuck events compared to an existing path-following solution.

Related News

Improving Generalization in Game Agents with Imitation Learning

SEED
Jul 16, 2024
How do we efficiently train in-game AI agents to handle new situations that they haven’t been trained on?

Towards Optimal Training Distribution for Photo-to-Face Models

SEED
Jul 8, 2024
How do we best construct game avatars from photos? This presentation discusses a work in progress with an optimized view of the training data.

Incorporating ML Research Into Audio Production: ExFlowSions Case Study

SEED
Jun 25, 2024
Mónica Villanueva and Jorge García present the challenges and lessons learned from turning a machine learning generative model from a research project into a game production tool.