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arXiv · 2608.09731

TAMS: Task-Aware Multi-View Adaptive Streaming for Wireless Telerobotic Manipulation

Zexin Deng·Zhenhui Yuan·Lu Tian·Subhash Lakshminarayana·Longhao Zou
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Abstract

Wireless telerobotic manipulation relies on timely multi-view video feedback, but the available uplink bandwidth is often limited and dynamic. This paper presents Task-Aware Multi-View Adaptive Streaming (TAMS), a system that allocates video bitrate according to the current manipulation phase. TAMS infers task phase from lightweight robot-side signals and prioritizes the camera view most relevant to the operator while preserving baseline visibility for secondary views. Experiments on a six-degree-of-freedom (6-DoF) teleoperation testbed under three constrained network conditions show that TAMS improves primary view Structural Similarity Index (SSIM), reduces task completion time, and increases trial success rate compared with equal and static allocation baselines. Under the most constrained bandwidth condition, TAMS reduces mean completion time from 68.9 s to 43.9 s relative to equal allocation and increases trial success rate from 48% to 71%. Code is available at: https://github.com/Dzxx623/TAMS.

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Zexin Deng, Zhenhui Yuan, Lu Tian, Subhash Lakshminarayana, Longhao Zou. 2026-08-10. TAMS: Task-Aware Multi-View Adaptive Streaming for Wireless Telerobotic Manipulation. https://arxiv.org/abs/2608.09731

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