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High-level programming and control for industrial robotics: using a hand-held accelerometer-based input device for gesture and posture recognition (1309.2093v1)

Published 9 Sep 2013 in cs.RO

Abstract: Purpose - Most industrial robots are still programmed using the typical teaching process, through the use of the robot teach pendant. This is a tedious and time-consuming task that requires some technical expertise, and hence new approaches to robot programming are required. The purpose of this paper is to present a robotic system that allows users to instruct and program a robot with a high-level of abstraction from the robot language. Design/methodology/approach - The paper presents in detail a robotic system that allows users, especially non-expert programmers, to instruct and program a robot just showing it what it should do, in an intuitive way. This is done using the two most natural human interfaces (gestures and speech), a force control system and several code generation techniques. Special attention will be given to the recognition of gestures, where the data extracted from a motion sensor (three-axis accelerometer) embedded in the Wii remote controller was used to capture human hand behaviours. Gestures (dynamic hand positions) as well as manual postures (static hand positions) are recognized using a statistical approach and artificial neural networks. Practical implications - The key contribution of this paper is that it offers a practical method to program robots by means of gestures and speech, improving work efficiency and saving time. Originality/value - This paper presents an alternative to the typical robot teaching process, extending the concept of human-robot interaction and co-worker scenario. Since most companies do not have engineering resources to make changes or add new functionalities to their robotic manufacturing systems, this system constitutes a major advantage for small- to medium-sized enterprises.

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Authors (3)
  1. Pedro Neto (37 papers)
  2. Norberto Pires (5 papers)
  3. Paulo Moreira (5 papers)
Citations (96)

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