الملخص
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Cable routing requires coordinated control of global cable topology and changing local contacts. We present CableVLA, an end-to-end multimodal vision-language-action framework that converts simulation-privileged supervision into deployable cable-topology and tactile representations. TopoHead distills node-level physics and current and future cable-topology information into causal visual context for the action expert. TacSense uses complementary frame and taxel branches to learn contact dynamics from resistive arrays, with simulator-derived kinematics and contact events providing supervision beyond the measured force map. A contact gate activates force-tactile residuals that refine the next 8 arm-and-gripper actions of a frozen topology-conditioned policy. Across 345 MuJoCo evaluations, CableVLA improves success from 62.6% for the $π_{0.5}$-V visual baseline to 84.9%. TacSense achieves pronounced gains in slip-transition recognition over a CNN-LSTM baseline with a similar parameter count, and this advantage persists under frozen-encoder probes. Topology prediction and 57-task tactile evaluations assess representation quality, while policy adaptation studies evaluate downstream control performance. Cross-simulator and real-robot comparisons further examine zero-shot policy transfer under changes in dynamics and sensing.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Teng, Z., Feng, B., Zou, X., Xiao, J., Li, M., Yin, Z., & Li, Y. (2026). CableVLA: تعلم تمثيل عالمي-محلي بامتياز المحاكاة لتوجيه الكابلات. https://omanscience.com/ar/articles/cablevla-simulation-privileged-global-local-representation-learning-for-cable-routing
MLA 9
Teng, Zhifei, et al. "CableVLA: تعلم تمثيل عالمي-محلي بامتياز المحاكاة لتوجيه الكابلات." https://omanscience.com/ar/articles/cablevla-simulation-privileged-global-local-representation-learning-for-cable-routing.
شيكاغو (المؤلف–التاريخ)
Teng, Zhifei, Bo Feng, Xiang Zou, Jinpeng Xiao, Min Li, Zhouping Yin, and Yiqun Li. 2026. "CableVLA: تعلم تمثيل عالمي-محلي بامتياز المحاكاة لتوجيه الكابلات." https://omanscience.com/ar/articles/cablevla-simulation-privileged-global-local-representation-learning-for-cable-routing.
هارفارد
Teng, Z., Feng, B., Zou, X., Xiao, J., Li, M., Yin, Z. and Li, Y. (2026) 'CableVLA: تعلم تمثيل عالمي-محلي بامتياز المحاكاة لتوجيه الكابلات', Available at: https://omanscience.com/ar/articles/cablevla-simulation-privileged-global-local-representation-learning-for-cable-routing.
فانكوفر
Teng Z, Feng B, Zou X, Xiao J, Li M, Yin Z, et al. CableVLA: تعلم تمثيل عالمي-محلي بامتياز المحاكاة لتوجيه الكابلات. https://omanscience.com/ar/articles/cablevla-simulation-privileged-global-local-representation-learning-for-cable-routing
IEEE
Z. Teng, B. Feng, X. Zou, J. Xiao, M. Li, Z. Yin, and Y. Li, "CableVLA: تعلم تمثيل عالمي-محلي بامتياز المحاكاة لتوجيه الكابلات," https://omanscience.com/ar/articles/cablevla-simulation-privileged-global-local-representation-learning-for-cable-routing.