Abstract
Slip detection is fundamental to dexterous manipulation, yet existing systems often lack precise characterization of detection latency and cross-platform generalization. We present SlipSense, a multimodal tactile slip-detection framework built on TacV5, a compact sensor integrating a $32 \times 32$ piezoresistive array operating at 240 Hz and a 3-axis MEMS accelerometer operating at 8 kHz. The piezoresistive array captures spatial pressure distributions, while the accelerometer captures friction-induced vibrations, providing complementary slip cues. The framework performs modality-specific encoding, intra-sensor fusion, and cross-modal attention with causal temporal prediction at 240 Hz. Experiments on a dataset of 1.4 million frames spanning 37 objects demonstrate the complementarity of the two modalities. SlipSense achieves 96.7% Macro F1 with a false-positive rate below 1.6%, detecting 76% of slip events within 23.1 ms. When trained solely on UMI data, SlipSense generalizes zero-shot to a Tesollo dexterous hand, transferring across unseen objects, distinct sensor units, and robotic platforms without retraining.
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Cite this article
APA 7
Jian, T., Kumar, A. T. S., Li, X. Y., Chen, Z., Dai, T., Sengul, A., Grimaldi, M., Lu, W., Nabi, S., & Yu, T. (2026). SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection. https://omanscience.com/en/articles/slipsense-multimodal-tactile-learning-for-low-latency-and-generalized-slip-detection
MLA 9
Jian, Tong, et al. "SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection." https://omanscience.com/en/articles/slipsense-multimodal-tactile-learning-for-low-latency-and-generalized-slip-detection.
Chicago (author–date)
Jian, Tong, Aditya Thurvas Senthil Kumar, Xin-Yi Li, Ziling Chen, Tianyu Dai, Ali Sengul, Matteo Grimaldi, Wenjie Lu, Saleh Nabi, and Tao Yu. 2026. "SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection." https://omanscience.com/en/articles/slipsense-multimodal-tactile-learning-for-low-latency-and-generalized-slip-detection.
Harvard
Jian, T., Kumar, A. T. S., Li, X. Y., Chen, Z., Dai, T., Sengul, A., Grimaldi, M., Lu, W., Nabi, S. and Yu, T. (2026) 'SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection', Available at: https://omanscience.com/en/articles/slipsense-multimodal-tactile-learning-for-low-latency-and-generalized-slip-detection.
Vancouver
Jian T, Kumar ATS, Li XY, Chen Z, Dai T, Sengul A, et al. SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection. https://omanscience.com/en/articles/slipsense-multimodal-tactile-learning-for-low-latency-and-generalized-slip-detection
IEEE
T. Jian, A. T. S. Kumar, X. Y. Li, Z. Chen, T. Dai, A. Sengul, M. Grimaldi, W. Lu, S. Nabi, and T. Yu, "SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection," https://omanscience.com/en/articles/slipsense-multimodal-tactile-learning-for-low-latency-and-generalized-slip-detection.