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Expanded Fingerprint Method for Analysis of Dynamic Cellular Actuator Arrays

[+] Author Affiliations
David MacNair, Jun Ueda

Georgia Institute of Technology, Atlanta, GA

Paper No. DSCC2012-MOVIC2012-8833, pp. 131-138; 8 pages
  • ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
  • Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems
  • Fort Lauderdale, Florida, USA, October 17–19, 2012
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4530-1
  • Copyright © 2012 by ASME


A key step along the way to understanding the natural motion is producing a physical, well understood actuator with a dynamic model closely resembling biological muscle. This actuator can then serve as the basis for building viable, full-strength, and safe muscles for disabled patients, human force amplification, and humanoid robotic systems. This paper presents an expanded fingerprint method for calculating the dynamic equations of motion for cellular actuator arrays, an actuator technology which combines many small flexible ‘cell’ actuator units for large-scale motion. The new method is simpler and quicker than generating the dynamic equations of motion from base principles, allows for fast recalculation for different and immense cell array structures, and provides an intuitive base for future controls work on cell array actuators. The paper also presents a physical SMA based cellular actuator array which, when compared with simulated results, matches the presented theory closely. Finally a brief discussion about the uses of the expanded fingerprint method, including controls and design work in robotics, is given. In the future, the theory will be used and extended to develop high degree-of-freedom cellular array actuated robotic devices with natural motion for use in rehabilitation, prosthesis development, human force amplification, and general robotics. These new devices will be especially effective at working safely around and with humans in complex human environments.

Copyright © 2012 by ASME



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