{"ID":2869350,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.14954","arxiv_id":"2509.14954","title":"Exploratory Movement Strategies for Texture Discrimination with a Neuromorphic Tactile Sensor","abstract":"We propose a neuromorphic tactile sensing framework for robotic texture classification that is inspired by human exploratory strategies. Our system utilizes the NeuroTac sensor to capture neuromorphic tactile data during a series of exploratory motions. We first tested six distinct motions for texture classification under fixed environment: sliding, rotating, tapping, as well as the combined motions: sliding+rotating, tapping+rotating, and tapping+sliding. We chose sliding and sliding+rotating as the best motions based on final accuracy and the sample timing length needed to reach converged accuracy. In the second experiment designed to simulate complex real-world conditions, these two motions were further evaluated under varying contact depth and speeds. Under these conditions, our framework attained the highest accuracy of 87.33\\% with sliding+rotating while maintaining an extremely low power consumption of only 8.04 mW. These results suggest that the sliding+rotating motion is the optimal exploratory strategy for neuromorphic tactile sensing deployment in texture classification tasks and holds significant promise for enhancing robotic environmental interaction.","short_abstract":"We propose a neuromorphic tactile sensing framework for robotic texture classification that is inspired by human exploratory strategies. Our system utilizes the NeuroTac sensor to capture neuromorphic tactile data during a series of exploratory motions. We first tested six distinct motions for texture classification un...","url_abs":"https://arxiv.org/abs/2509.14954","url_pdf":"https://arxiv.org/pdf/2509.14954v1","authors":"[\"Xingchen Xu\",\"Ao Li\",\"Benjamin Ward-Cherrier\"]","published":"2025-09-18T13:38:47Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[\"LoRA\"]","has_code":false}