TY - GEN
T1 - Brain-Inspired Visual Language Navigation Robot Position Deviation Correction
AU - Li, Zhiyuan
AU - Tu, Ziqin
AU - Zhang, Meixin
AU - Lu, Yanfeng
AU - Qiao, Hong
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - This research addresses the limitations of traditional visual and verbal navigation (VLN) tasks by introducing an innovative RFID-based, brain-inspired route correction scheme. This system integrates visual, voice, RFID, and odometer sensors to tackle real-world navigation challenges such as lighting changes and hardware errors. By combining the brain’s grid coding and spatial perception mechanisms with RFID technology, we achieve precise location tracking. Additionally, a PID controller simulates the brain’s perception of spatial edges, providing real-time deviation correction for the agent. Moreover, a reinforcement learning-based path planning method, enhanced with domain randomization, ensures continuous navigation. This approach, validated through VLN simulations, significantly improves navigation accuracy and success rates without incurring high learning costs, marking substantial progress in robot navigation technology.
AB - This research addresses the limitations of traditional visual and verbal navigation (VLN) tasks by introducing an innovative RFID-based, brain-inspired route correction scheme. This system integrates visual, voice, RFID, and odometer sensors to tackle real-world navigation challenges such as lighting changes and hardware errors. By combining the brain’s grid coding and spatial perception mechanisms with RFID technology, we achieve precise location tracking. Additionally, a PID controller simulates the brain’s perception of spatial edges, providing real-time deviation correction for the agent. Moreover, a reinforcement learning-based path planning method, enhanced with domain randomization, ensures continuous navigation. This approach, validated through VLN simulations, significantly improves navigation accuracy and success rates without incurring high learning costs, marking substantial progress in robot navigation technology.
KW - Grid Coding
KW - RFID
KW - Vision-Language Navigation
UR - https://www.scopus.com/pages/publications/85218445644
U2 - 10.1007/978-981-96-0789-1_20
DO - 10.1007/978-981-96-0789-1_20
M3 - 会议稿件
AN - SCOPUS:85218445644
SN - 9789819607884
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 273
EP - 287
BT - Intelligent Robotics and Applications - 17th International Conference, ICIRA 2024, Proceedings
A2 - Lan, Xuguang
A2 - Mei, Xuesong
A2 - Jiang, Caigui
A2 - Zhao, Fei
A2 - Tian, Zhiqiang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th International Conference on Intelligent Robotics and Applications, ICIRA 2024
Y2 - 31 July 2024 through 2 August 2024
ER -