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arXiv · 1910.00127

A Mobile Manipulation System for One-Shot Teaching of Complex Tasks in Homes

Max Bajracharya·James Borders·Dan Helmick·Thomas Kollar·Michael Laskey·John Leichty·Jeremy Ma·Umashankar Nagarajan·Akiyoshi Ochiai·Josh Petersen·Krishna Shankar·Kevin Stone·Yutaka Takaoka
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Abstract

We describe a mobile manipulation hardware and software system capable of autonomously performing complex human-level tasks in real homes, after being taught the task with a single demonstration from a person in virtual reality. This is enabled by a highly capable mobile manipulation robot, whole-body task space hybrid position/force control, teaching of parameterized primitives linked to a robust learned dense visual embeddings representation of the scene, and a task graph of the taught behaviors. We demonstrate the robustness of the approach by presenting results for performing a variety of tasks, under different environmental conditions, in multiple real homes. Our approach achieves 85% overall success rate on three tasks that consist of an average of 45 behaviors each.

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Max Bajracharya, James Borders, Dan Helmick, Thomas Kollar, Michael Laskey, John Leichty, Jeremy Ma, Umashankar Nagarajan, Akiyoshi Ochiai, Josh Petersen, Krishna Shankar, Kevin Stone, Yutaka Takaoka. 2020-03-03. A Mobile Manipulation System for One-Shot Teaching of Complex Tasks in Homes. https://arxiv.org/abs/1910.00127

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