Abstract
Reaching ability is a kind of human sensory motor coordination. The objective of this work is to imitate the developmental progress of human infant to create a robotic system which can reach or capture objects. The work proposes to employ a double neural network architecture to implement control a robotic system to learn reaching within 3D experimental environment. A constraint releasing mechanism is applied to implement the development procedure for the robot system. In addition, the experimental results are described and discussed in this paper.
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Chao, F., Hu, L., Shi, M., Jiang, M. (2011). Robotic 3D Reaching through a Development-Driven Double Neural Network Architecture. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_24
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DOI: https://doi.org/10.1007/978-3-642-25661-5_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25660-8
Online ISBN: 978-3-642-25661-5
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