Evaluating a Hybrid LLM Q-Learning/DQN Framework for Adaptive Obstacle Avoidance in Embedded Robotics
This paper introduces a pioneering hybrid framework that integrates Q-learning/deep Q-network (DQN) with a locally deployed large language model (LLM) to enhance obstacle avoidance in embedded robotic systems. The STM32WB55RG microcontroller handles real-time decision-making using sensor data, while...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | AI |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-2688/6/6/115 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|