High‐level programming and control for industrial robotics: using a hand‐held accelerometer‐based input device for gesture and posture recognition
Author:
Neto Pedro,Norberto Pires J.,Paulo Moreira A.
Abstract
PurposeMost 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/approachThe 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.FindingsIt is shown that the robotic system presented is suitable to enable users without programming expertise to rapidly create robot programs. The experimental tests showed that the developed system can be customized for different users and robotic platforms.Research limitations/implicationsThe proposed system is tested on two different robotic platforms. Since the options adopted are mainly based on standards, it can be implemented with other robot controllers without significant changes. Future work will focus on improving the recognition rate of gestures and continuous gesture recognition.Practical implicationsThe 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/valueThis 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.
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Control and Systems Engineering
Reference28 articles.
1. Akmeliawati, R., Ooi, M.P.L. and Kuang, Y.C. (2007), “Real‐time Malaysian sign language translation using colour segmentation and neural network”, Instrumentation and Measurement Technology Conference (IMTC 2007), pp. 1‐6. 2. Aleotti, J., Skoglund, A. and Duckett, T. (2004), “Position teaching of a robot arm by demonstration with a wearable input device”, paper presented at the International Conference on Intelligent Manipulation and Grasping (IMG04), Genoa. 3. Bischoff, R., Kazi, A. and Seyfarth, M. (2002), “The MORPHA style guide for icon‐based programming”, The 11th IEEE International Symposium on Robot and Human Interactive Communication, pp. 482‐7. 4. Calcagno, R., Rusina, F., Deregibus, F., Vincentelli, A.S. and Bonivento, A. (2006), “Applications of wireless technologies in automotive production systems”, VDI Berichte, Vol. 1956, pp. 57‐8. 5. Chen, X., Zhang, X., Zhao, Z., Yang, J., Lantz, V. and Wang, K. (2007), “Hand gesture recognition research based on surface EMG sensors and 2D‐accelerometrs”, 11th IEEE International Symposium on Wearable Computers, pp. 11‐14.
Cited by
58 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|