Abstract
Tactile feedback provides embodied agents with physical information beyond visual observations, enabling more reliable interaction with the real world. However, despite the rapid progress of vision-tactile-language-action (VTLA) policies, there remains a lack of unified benchmarks for evaluating tactile-enabled robot manipulation across simulation and the real world. To address this gap, we introduce OpenViTac, a visuo-tactile manipulation benchmark for evaluating robot policies across simulation and the real world. OpenViTac organizes contact-rich manipulation into four tactile-relevant capability dimensions and provides paired simulation-real-world settings for consistent evaluation of VLA, WAM, and VTLA policies. Building upon this benchmark, we investigate how different tactile representations and integration strategies affect the performance of pretrained VLA models. Correspondingly, we introduce OpenVTLA, a tactile augmentation framework that combines the best-performing representation and integration strategy. Furthermore, we leverage the paired benchmark setting to study sim-real co-training and analyze factors affecting cross-domain policy learning. Together, OpenViTac provides a unified platform for evaluating and advancing visuo-tactile robot manipulation.
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- Green open access
Cite this article
APA 7
Wu, Y., Li, Q., Min, N., Zhong, G., Zhao, H., Li, Z., Xu, H., Xu, S., Lin, X., Diao, Z., Liu, Z., Lian, S., Lu, S., Zhao, S., Ye, Z., Wu, Z., & Jiang, Y. G. (2026). OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework. https://omanscience.com/en/articles/openvitac-learning-and-benchmarking-visuo-tactile-policies-in-a-unified-sim-and-real-framework
MLA 9
Wu, Yifan, et al. "OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework." https://omanscience.com/en/articles/openvitac-learning-and-benchmarking-visuo-tactile-policies-in-a-unified-sim-and-real-framework.
Chicago (author–date)
Wu, Yifan, Qin Li, Nan Min, Guojin Zhong, Haoyu Zhao, Zhiyuan Li, Houze Xu, Shengqi Xu, Xingyao Lin, Zijie Diao, Zhaoxiang Liu, Shiguo Lian, Shunlin Lu, Shihao Zhao, Ziyi Ye, Zuxuan Wu, and Yu-Gang Jiang. 2026. "OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework." https://omanscience.com/en/articles/openvitac-learning-and-benchmarking-visuo-tactile-policies-in-a-unified-sim-and-real-framework.
Harvard
Wu, Y., Li, Q., Min, N., Zhong, G., Zhao, H., Li, Z., Xu, H., Xu, S., Lin, X., Diao, Z., Liu, Z., Lian, S., Lu, S., Zhao, S., Ye, Z., Wu, Z. and Jiang, Y. G. (2026) 'OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework', Available at: https://omanscience.com/en/articles/openvitac-learning-and-benchmarking-visuo-tactile-policies-in-a-unified-sim-and-real-framework.
Vancouver
Wu Y, Li Q, Min N, Zhong G, Zhao H, Li Z, et al. OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework. https://omanscience.com/en/articles/openvitac-learning-and-benchmarking-visuo-tactile-policies-in-a-unified-sim-and-real-framework
IEEE
Y. Wu, Q. Li, N. Min, G. Zhong, H. Zhao, Z. Li, H. Xu, S. Xu, X. Lin, Z. Diao, Z. Liu, S. Lian, S. Lu, S. Zhao, Z. Ye, Z. Wu, and Y. G. Jiang, "OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework," https://omanscience.com/en/articles/openvitac-learning-and-benchmarking-visuo-tactile-policies-in-a-unified-sim-and-real-framework.