Contextual awareness: Understanding monologic natural language instructions for autonomous robots
Contextual awareness: Understanding monologic natural language instructions for autonomous robots
复制标题
情境意识：理解自主机器人的单一自然语言指令
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
T. Howard
中科院分区：
文献类型：
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作者：
Jacob Arkin;Matthew R. Walter;Adrian Boteanu;Michael E. Napoli;Harel Biggie;H. Kress;T. Howard
如今，有许多人类和机器人定期在各种领域进行相互作用的例子，例如制造，协调组装和康复。对更普遍可访问的沟通界面的需求促使了一些最近的独立研究工作，重点是为机器人系统提供强大的自然语言界面。自然语言接口可以为未经训练和非专家用户提供直观的互动。但是，实现实时绩效特别具有挑战性，但至关重要，以实现灵活，有效的沟通。语言输入的长度直接影响运行时性能，并且当输入是多个句子或独白的序列时，很快就成为一个实际问题。在这项工作中，我们提出了一种当代概率图形模型的变体，用于语言理解，该模型将输入的新颖分割介绍为要按顺序标记的一系列句子。我们介绍了不断更新的先前上下文的概念，该上下文在推理过程中保留了先前句子的含义。在以后的句子评估期间，这种先前的上下文是证据。我们评估了两个自然语言语料库的模型，并在Clearpath Husky A200移动操纵器和模拟的Rethink Robotics Baxter Baxter机器人上演示了其实用性。
Today, there are many examples of humans and robots regularly interacting in a variety of domains, such as manufacturing, coordinated assembly, and rehabilitation. A resulting demand for more generally accessible communication interfaces has motivated several recent independent research efforts focused on providing robotic systems with a robust natural language interface. Natural language interfaces enable intuitive interaction for untrained and non-expert users. However, achieving real-time performance is particularly challenging, yet essential, to enable flexible, efficient communication. The length of the language input directly impacts the run-time performance and quickly becomes a practical issue when the input is a sequence of multiple sentences, or a monologue. In this work, we propose a variant of a contemporary probabilistic graphical model for language understanding that introduces novel segmentation of the input into a sequence of sentences to be labeled in order. We introduce the notion of a continuously updated prior context that retains the meaning of previous sentences as the inference process proceeds. This prior context serves as evidence during future sentence evaluations. We evaluate our model on two natural language corpora, and demonstrate its utility on a Clearpath Husky A200 mobile manipulator and a simulated Rethink Robotics Baxter Robot.