NDLI: LAP: A Human-in-the-loop Adaptation Approach for Industrial Robots

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LAP: A Human-in-the-loop Adaptation Approach for Industrial Robots

Content Provider	ACM Digital Library
Author	Tee, Keng Peng Ko, Wilson K.H. Wu, Yan
Abstract	In the last few years, a shift from mass production to mass customisation is observed in the industry. Easily reprogrammable robots that can perform a wide variety of tasks are desired to keep up with the trend of mass customisation while saving costs and development time. Learning by Demonstration (LfD) is an easy way to program the robots in an intuitive manner and provides a solution to this problem. In this work, we discuss and evaluate LAP, a three-stage LfD method that conforms to the criteria for the high-mix-low-volume (HMLV) industrial settings. The algorithm learns a trajectory in the task space after which small segments can be adapted on-the-fly by using a human-in-the-loop approach. The human operator acts as a high-level adaptation, correction and evaluation mechanism to guide the robot. This way, no sensors or complex feedback algorithms are needed to improve robot behaviour, so errors and inaccuracies induced by these subsystems are avoided. After the system performs at a satisfactory level after the adaptation, the operator will be removed from the loop. The robot will then proceed in a feed-forward fashion to optimise for speed. We demonstrate this method by simulating an industrial painting application. A KUKA LBR iiwa is taught how to draw an eight figure which is reshaped by the operator during adaptation.
Starting Page	313
Ending Page	319
Page Count	7
File Format	PDF
ISBN	9781450345088
DOI	10.1145/2974804.2974805
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Automation Intuitive teaching Imitation learning Human-robot interaction Industrial robots Robot learning from demonstration Industrial robotics
Content Type	Text
Resource Type	Article

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