VR実演と知識推論によるロボットプログラム自動生成
Knowledge-Driven Robot Program Synthesis from Human VR Demonstrations
人間がVR空間で行った作業実演を常識知識と物理シミュレーションで意味解釈し、ロボット制御プログラムを自動生成するシステムを提案した。買い物アシストロボットの力覚を伴う運搬・配置タスクで実証した。
著者: Benjamin Alt, Franklin Kenghagho Kenfack, Andrei Haidu, Darko Katic, Rainer Jäkel, Michael Beetz
分類: cs.RO, cs.AI
原文アブストラクト
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 https://github.com/ease-crc/vr-program-synthesis.
