Qingao Chai — accepted AI-conference papers

2025

Brain-Inspired Spatial Continuous State Encoding for Efficient Spiking-Based Navigation

Qingao Chai, Jiashuo Wang, Runhao Jiang, Bo Yang, Rui Yan, Huajin Tang

ICRA 2025

Spiking neural networks (SNNs) show great potential in mapless navigation tasks due to their low power consumption, but the continuous representation of spatial information poses a challenge to SNN training. Neuroscience findings reveal that spatial cognition cells encode spatial information through

Cited by 1 Source ↗Scholar ↗

2025

HSRL: A Hierarchical Control System Based on Spiking Deep Reinforcement Learning for Robot Navigation

Bo Yang, Shibo Zhou, Chaohui Lin, Qingao Chai, Rui Yan, De Ma +2

ICRA 2025

Reinforcement Learning (RL) has shown promise in robotic navigation tasks, yet applying it to real-world environments remains challenging due to dynamic complexities and the need for dynamically feasible actions. We propose a hierarchical control framework based on Spiking Deep Reinforcement Learnin

Cited by 3 Source ↗Scholar ↗