الملخص
Tactile information is essential for contact-rich manipulation tasks in robotics. Vision-based tactile sensors make it particularly easy to design end-to-end manipulation policies with tactile sensing, as they enable the use of existing encoders from computer vision. However, this has led to a huge variety of architectures, training datasets, and evaluation protocols, making it difficult to determine which design choices best encode touch. In this work, we address this gap and present a comprehensive study of tactile encoders and fusion strategies across various contact-rich manipulation tasks in real-world experiments. To enable a controlled comparison, we train and evaluate all models under the same pipeline and experimental setup, comprising more than 2000 real-world rollouts. Our results go beyond other studies that only compare simulation performance, which does not necessarily translate to real-world settings, where large-scale evaluations are needed to obtain reliable statistics. Our key finding is that there is no universally optimal representation or fusion strategy for encoding visual-tactile. Instead, the best encoder backbone and fusion scheme depend strongly on the task.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Bien, S., Makowski, D. O., Kneissl, C., Mirjalili, R., Vanjani, P., Lioutikov, R., Kutyniok, G., Walter, F., & Burgard, W. (2026). TACTIC: Understanding Tactile Encoders and Conditioning for Contact-rich Robot Manipulation Policies. https://omanscience.com/ar/articles/tactic-understanding-tactile-encoders-and-conditioning-for-contact-rich-robot-manipulation-policies
MLA 9
Bien, Seongjin, et al. "TACTIC: Understanding Tactile Encoders and Conditioning for Contact-rich Robot Manipulation Policies." https://omanscience.com/ar/articles/tactic-understanding-tactile-encoders-and-conditioning-for-contact-rich-robot-manipulation-policies.
شيكاغو (المؤلف–التاريخ)
Bien, Seongjin, Débora Oliveira Makowski, Carlo Kneissl, Reihaneh Mirjalili, Pankhuri Vanjani, Rudolf Lioutikov, Gitta Kutyniok, Florian Walter, and Wolfram Burgard. 2026. "TACTIC: Understanding Tactile Encoders and Conditioning for Contact-rich Robot Manipulation Policies." https://omanscience.com/ar/articles/tactic-understanding-tactile-encoders-and-conditioning-for-contact-rich-robot-manipulation-policies.
هارفارد
Bien, S., Makowski, D. O., Kneissl, C., Mirjalili, R., Vanjani, P., Lioutikov, R., Kutyniok, G., Walter, F. and Burgard, W. (2026) 'TACTIC: Understanding Tactile Encoders and Conditioning for Contact-rich Robot Manipulation Policies', Available at: https://omanscience.com/ar/articles/tactic-understanding-tactile-encoders-and-conditioning-for-contact-rich-robot-manipulation-policies.
فانكوفر
Bien S, Makowski DO, Kneissl C, Mirjalili R, Vanjani P, Lioutikov R, et al. TACTIC: Understanding Tactile Encoders and Conditioning for Contact-rich Robot Manipulation Policies. https://omanscience.com/ar/articles/tactic-understanding-tactile-encoders-and-conditioning-for-contact-rich-robot-manipulation-policies
IEEE
S. Bien, D. O. Makowski, C. Kneissl, R. Mirjalili, P. Vanjani, R. Lioutikov, G. Kutyniok, F. Walter, and W. Burgard, "TACTIC: Understanding Tactile Encoders and Conditioning for Contact-rich Robot Manipulation Policies," https://omanscience.com/ar/articles/tactic-understanding-tactile-encoders-and-conditioning-for-contact-rich-robot-manipulation-policies.