外观
论文arXiv 2610.2199913 天前
VP-EVT：面向具身视觉跟踪的主动可见性保持
原文链接：VP-EVT: Active Visibility Preservation for Embodied Visual Tracking（arXiv 2610.21999 · 发布日期：2026-10-15）
VP-EVT: Active Visibility Preservation for Embodied Visual Tracking
VP-EVT将目标可见性显式纳入运动控制，结合语言引导感知与历史估计，在OccEVT-Bench闭环遮挡评估中验证。
核心要点
- 动态场景中行人持续遮挡使反应式EVT方法易长时间丢失目标。
- 框架分离目标与行人观测，融合视觉历史和自运动估计相对位置与运动。
- 依据跟随航点预测遮挡风险，低风险保留原动作，高风险用循环控制器调整视角。
- 提出OccEVT-Bench并采集专家演示；Risk split三项指标均优于竞争基线。
验证范围与局限：验证范围为OccEVT-Bench上的持久遮挡闭环评估，摘要未说明真机验证。
英文摘要 (Abstract)
Embodied Visual Tracking (EVT) is an essential capability for intelligent robots in human-robot collaboration, requiring an agent to follow a designated target person in dynamic environments relying solely on egocentric visual perception. However, persistent pedestrian occlusions in dynamic scenes pose critical challenges to existing EVT methods. Lacking proactive visibility preservation, reactive tracking methods frequently experience prolonged target loss under severe occlusions. Therefore, we propose VP-EVT, a framework that treats target visibility as an explicit objective of motion control rather than a by-product of following. Acting on this objective requires understanding both what obstructs the target and how robot motion can change that obstruction. VP-EVT therefore uses language-guided perception to extract separate target and pedestrian observations. When occlusion makes current observations incomplete, VP-EVT combines visual history with ego-motion to maintain estimates of their relative positions and motion. Using these estimates and the current following waypoints, VP-EVT predicts whether continued following will sustain the obstruction. When the predicted risk is low, the original following motion is retained; otherwise, a recurrent controller combines updated estimates with maneuver context from preceding decisions to coordinate viewpoint adjustment and the return to stable following. Moreover, we introduce OccEVT-Bench for closed-loop evaluation of persistent occlusion and collect expert demonstrations for training. On its Risk split, VP-EVT improves success rate by 121.4% relative to a competitive baseline and reduces visibility deficit and longest target-loss duration by 78.8% and 74.4%, respectively.
作者：Yanci Wen, Tianle Zeng, Jianwei Peng, Weixi Situ, Hanjing Ye, Hong Zhang
来源
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