Aging societies, labor shortages and increasing wage costs call for
assistance robots capable of autonomously performing a wide array of real-world
tasks. Such open-ended robotic manipulation requires not only powerful
knowledge representations and reasoning (KR&R) algorithms, but also methods for
humans to instruct robots what tasks to perform and how to perform them. In
this paper, we present a system for automatically generating executable robot
control programs from human task demonstrations in virtual reality (VR). We
leverage common-sense knowledge and game engine-based physics to semantically
interpret human VR demonstrations, as well as an expressive and general task
representation and automatic path planning and code generation, embedded into a
state-of-the-art cognitive architecture. We demonstrate our approach in the
context of force-sensitive fetch-and-place for a robotic shopping assistant.
The source code is available at
this https URL

本文介绍了一种通过虚拟现实人类任务演示自动生成可执行机器人控制程序的系统，利用常识知识和基于游戏引擎的物理，以及自动路径规划和代码生成，实现了具有表现力和通用性的任务表示，在强力抓取和放置机器人购物助手的场景中进行了演示。