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Jul, 2017
通过 Push 提议网络学习物体分离
Learning to Singulate Objects using a Push Proposal Network
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Andreas Eitel, Nico Hauff, Wolfram Burgard
TL;DR
使用基于神经网络的方法从具有随机布局的桌面场景采集的数据中训练模型，通过选择合适的推动动作来将未知物体从杂乱的环境中分离，实现机器人在无序环境下执行任务的高成功率和低推动次数。
Abstract
A key challenge for manipulation in unstructured environments is action selection. We present a novel
neural network
-based approach that separates
unknown objects
in clutter by selecting favourable
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