Lightweight ANNs replicate CANN neurodynamics for HDCs and GCs to deliver dead-reckoning path integration that matches NeuroSLAM accuracy while cutting compute by 17.5% on general devices and 40-50% on edge devices.
A review of brain -inspired cognition and navigation technology for mobile robots
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Boosting Brain-inspired Path Integration Efficiency via Learning-based Replication of Continuous Attractor Neurodynamics
Lightweight ANNs replicate CANN neurodynamics for HDCs and GCs to deliver dead-reckoning path integration that matches NeuroSLAM accuracy while cutting compute by 17.5% on general devices and 40-50% on edge devices.