Action graphs for proactive robot assistance in smart environments
Action graphs for proactive robot assistance in smart environments
复制标题
智能环境中主动机器人协助的动作图
DOI：
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复制
发表时间：
2020
影响因子：
1.7
通讯作者：
P. Simoens
中科院分区：
文献类型：
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作者：
Helen Harman;P. Simoens
智能环境已经可以通过无处不在的传感器观察人类的行为。基于这些观察，我们的工作旨在预测人类下一步可能执行的动作。预测可以使机器人通过代表人类自主执行动作来主动协助人类。在本文中，动作图被引入到模型之间的顺序约束的行动。行动图是从规划领域定义语言（PDDL）中定义的问题中导出的。当观察到一个动作时，节点值会被更新，并预测下一个动作。随后，机器人执行预测的动作之一，如果它不通过阻碍或延迟它们来影响人类的流动。我们的动作图方法被应用到厨房领域。
Smart environments can already observe the actions of a human through pervasive sensors. Based on these observations, our work aims to predict the actions a human is likely to perform next. Predictions can enable a robot to proactively assist humans by autonomously executing an action on their behalf. In this paper, Action Graphs are introduced to model the order constraints between actions. Action Graphs are derived from a problem defined in Planning Domain Definition Language (PDDL). When an action is observed, the node values are updated and next actions predicted. Subsequently, a robot executes one of the predicted actions if it does not impact the flow of the human by obstructing or delaying them. Our Action Graph approach is applied to a kitchen domain.
DOI：
10.3390/s19030646
发表时间：
2019-02
期刊：
Sensors (Basel, Switzerland)
影响因子：
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作者：
Kristina Yordanova;S. Lüdtke;Samuel Whitehouse;Frank Krüger;A. Paiement;M. Mirmehdi;I. Craddock;T. Kirste
通讯作者：
Kristina Yordanova;S. Lüdtke;Samuel Whitehouse;Frank Krüger;A. Paiement;M. Mirmehdi;I. Craddock;T. Kirste