Integrating Radar-Based Obstacle Detection with Deep Reinforcement Learning for Robust Autonomous Navigation

Integrating Radar-Based Obstacle Detection with Deep Reinforcement Learning for Robust Autonomous Navigation

This study presents an approach to autonomous navigation for wheeled robots, combining radar-based dynamic obstacle detection with a BiGRU-based deep reinforcement learning (DRL) framework. Using filtering and tracking algorithms, the proposed system leverages radar sensors to cluster object points...

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Bibliographic Details
Main Authors: Nabih Pico, Estrella Montero, Maykoll Vanegas, Jose Miguel Erazo Ayon, Eugene Auh, Jiyou Shin, Myeongyun Doh, Sang-Hyeon Park, Hyungpil Moon
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
autonomous navigation
radar sensors
dynamic obstacles
deep reinforcement learning
Online Access:https://www.mdpi.com/2076-3417/15/1/295
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