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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/9539

Title: Biologically Inspired Control for Robotic Arm Using Neural Oscillator Network
Authors: Yang, Woosung
Bae, Ji-Hun
Oh, Yonghwan
Chong, Nak Young
You, Bum Jae
Keywords: Bio-inspired control
natural dynamics
neural oscillators
external disturbance
Issue Date: 2009-10
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009
Start page: 135
End page: 141
DOI: 10.1109/IROS.2009.5354357
Abstract: It is known that biologically inspired neural systems could exhibit natural dynamics efficiently and robustly for motion control, especially for rhythmic motion tasks. Inaddition, humans or animals exhibit natural adaptive motionswithout considering their kinematic configurations againstunexpected disturbances or environment changes. In this paper, we focus on rhythmic arm motions that can be achieved by using a controller based on neural oscillators and virtual force. In comparison with conventional researches, this work treats neither trajectories planning nor inverse kinematics. Instead of those, a few desired points in task-space and a control method with Jacobian transpose and joint velocity damping are merely adopted. In addition, if the joints of robotic arms are coupled toneural oscillators, they may be capable of achieving biologically inspired motions corresponding to environmental changes. To verify the proposed control scheme, we perform some simulations to trace a desired motion and show the potential features related with self-adaptation that enables a three-link planar arm to make adaptive changes from the given motion to a compliant motion. Specifically, we investigate that human-likemovements and motion repeatability are satisfied underkinematic redundancy of joints.
Rights: Copyright (C) 2009 IEEE. Reprinted from IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009, , 2009, 135-141. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
URI: http://hdl.handle.net/10119/9539
Material Type: publisher
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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