【24h】

Complex Task Learning from Unstructured Demonstrations

机译:从非结构化演示中学习复杂的任务

获取原文

摘要

A simple system that allows end-users to intuitively program robots is a key step in getting robots out of the laboratory and into the real world. Although in many cases it is possible for an expert to successfully program a robot to perform complex tasks, such programming requires a great deal of knowledge, is time-consuming, and is often task-specific. In response to this, much recent work has focused on robot learning from demonstration (LfD) (Argall et al. 2009; Billard et al. 2008), where non-expert users can teach a robot how to perform a task by example. Such demonstrations eliminate the need for knowledge of the robotic system, and in many cases, require only a fraction of the time that it would take an expert to design a controller by hand.
机译:一个简单的系统,允许最终用户直观地编程机器人是让机器人从实验室和现实世界中获得机器人的关键步骤。虽然在许多情况下,专家可以成功地编程机器人来执行复杂的任务,但这种编程需要大量的知识,是耗时的,并且通常是特定于任务的。回应这一点,最近的工作侧重于从示范(LFD)的机器人学习(Argall等,2009; Billard等,2008),其中非专家用户可以通过示例教授如何执行任务。这种示威活动消除了对机器人系统的知识的需要,并且在许多情况下,只需要一小部分,即将使用专家手工设计控制器的时间。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号