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Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation
Published on: October 8, 2011
Xiaomao Zhou1, Yanbin Gao2, Lianwu Guan3
1College of Automation, Harbin Engineering University, Harbin 150001, China. zhouxiaomao@hrbeu.edu.cn.
This study introduces a novel robot navigation system combining goal-directed end-to-end learning for global planning and deep reinforcement learning (RL) for local planning. This hybrid approach enhances adaptability and efficiency in robot navigation tasks.
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