机器人活动多视角进展预测
Multiview Progress Prediction of Robot Activities
AI总结：
本文提出了一种多视角架构，用于机器人操作任务中的动作进展预测，以提高机器人与人类协同工作的有效性和安全性。
摘要：
为使机器人能够有效地与人类协同工作，它们必须能够理解正在进行的动作的进展。这种能力，称为动作进展预测，对于及时帮助和自主决策等任务至关重要。然而，机器人中动作进展建模往往被忽视。此外，单个摄像头可能不足以理解机器人的自身动作，因为自遮挡会显著阻碍感知和模型性能。在本文中，我们提出了一种多视角架构，用于机器人操作任务中的动作进展预测。在Mobile ALOHA上的实验展示了所提出方法的有效性。
英文摘要：
For robots to operate effectively and safely alongside humans, they must be able to understand the progress of ongoing actions. This ability, known as action progress prediction, is critical for tasks ranging from timely assistance to autonomous decision-making. However, modeling action progression in robotics has often been overlooked. Moreover, a single camera may be insufficient for understanding robot's ego-actions, as self-occlusion can significantly hinder perception and model performance. In this paper, we propose a multi-view architecture for action progress prediction in robot manipulation tasks. Experiments on Mobile ALOHA demonstrate the effectiveness of the proposed approach.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
