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Redefining cross-modal fusion at the prototype level, ProtoHGF-Net significantly enhances target detection by suppressing background noise.
Personalized haptic feedback can be learned from just a few user demonstrations, transforming how robots adapt to individual safety preferences in real-time.
High-risk obstacles can now dynamically influence safety margins in real-time navigation, enhancing both teleoperation and autonomous control.
