L-VITeX: Light-weight Visual Intuition for Terrain Exploration
Mazumder, Antar, Madhiha, Zarin Anjum
–arXiv.org Artificial Intelligence
This paper presents L-VITeX, a lightweight visual intuition system for terrain exploration designed for resource-constrained robots and swarms. L-VITeX aims to provide a hint of Regions of Interest (RoIs) without computationally expensive processing. By utilizing the Faster Objects, More Objects (FOMO) tinyML architecture, the system achieves high accuracy (>99%) in RoI detection while operating on minimal hardware resources (Peak RAM usage < 50 KB) with near real-time inference (<200 ms). The paper evaluates L-VITeX's performance across various terrains, including mountainous areas, underwater shipwreck debris regions, and Martian rocky surfaces. Additionally, it demonstrates the system's application in 3D mapping using a small mobile robot run by ESP32-Cam and Gaussian Splats (GS), showcasing its potential to enhance exploration efficiency and decision-making.
arXiv.org Artificial Intelligence
Oct-10-2024
- Country:
- North America > United States (0.14)
- Asia > Bangladesh
- Dhaka Division > Dhaka District > Dhaka (0.04)
- Genre:
- Research Report (0.82)
- Technology:
- Information Technology > Artificial Intelligence
- Vision (1.00)
- Robots
- Locomotion (0.67)
- Autonomous Vehicles (0.47)
- Machine Learning
- Performance Analysis > Accuracy (0.47)
- Neural Networks > Deep Learning (0.47)
- Information Technology > Artificial Intelligence