DocumentCode
88377
Title
Averaging Tail-Actuated Robotic Fish Dynamics Through Force and Moment Scaling
Author
Jianxun Wang ; Xiaobo Tan
Author_Institution
Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
Volume
31
Issue
4
fYear
2015
fDate
Aug. 2015
Firstpage
906
Lastpage
917
Abstract
Averaging of robotic fish dynamics is of interest for the purposes of path planning and controller design due to the rhythmic movement of the robot. For a faithful dynamic model of robotic fish, however, classical averaging or geometric averaging typically cannot produce an average model that is accurate and in the meantime amenable to analysis or control design. In this paper, a novel averaging approach is proposed for tail-actuated robotic fish dynamics, in which the tail-generated hydrodynamic force is modeled with the Lighthill´s large-amplitude elongated-body theory. The approach consists of scaling the force and moment terms and, then, conducting classical averaging. Numerical investigation reveals that the scaling function for the force term is a constant independent of tail-beat patterns, while the scaling function for the moment term depends linearly on the tail-beat bias. Extensive simulation and experimental results, comparing the predictions from the original and average models, are presented to support the effectiveness of the averaging approach. Existence and local stability of the equilibria for the average model are further analyzed. These equilibria are subsequently used to obtain an analytical solution for steady turning parameters, such as turning period and turning radius, without running simulation of the original or average dynamic models.
Keywords
biomimetics; control system synthesis; hydrodynamics; mobile robots; path planning; robot dynamics; stability; analytical solution; average model equilibria; averaging tail-actuated robotic fish dynamics; controller design; force scaling; geometric averaging; large-amplitude elongated-body theory; local stability; moment scaling; moment term; path planning; rhythmic robot movement; scaling function; steady turning parameters; tail-beat bias; tail-beat patterns; tail-generated hydrodynamic force; turning period; turning radius; Analytical models; Dynamics; Force; Mathematical model; Predictive models; Robots; Turning; Averaging; biologically inspired robots; dynamics; marine robotics; robotic fish;
fLanguage
English
Journal_Title
Robotics, IEEE Transactions on
Publisher
ieee
ISSN
1552-3098
Type
jour
DOI
10.1109/TRO.2015.2433539
Filename
7117447
Link To Document