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Title: Distributed sensing for fluid disturbance compensation and motion control of intelligent robots
A control methodology for aerial or aquatic vehicles is presented that leverages intelligent distributed sensing inspired by the lateral line found in fish to directly measure the fluid forces acting on the vehicle. As a result, the complex robot control problem is effectively simplified to that of a rigid body in a vacuum. Furthermore, by sensing these forces, they can be compensated for immediately, rather than after they have displaced the vehicle. We have created a sensory shell around a prototype autonomous underwater vehicle, derived algorithms to remove static pressure and calculate total force from the discrete measurements using a fitting technique that filters sensor error, and validated the control methodology on a vehicle in the presence of multiple fluid disturbances. This sensing control scheme reduces position tracking errors by as much as 72% compared to a standard position error feedback controller.  more » « less
Award ID(s):
1638034
NSF-PAR ID:
10112894
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Nature machine intelligence
Volume:
1
Issue:
May
ISSN:
2522-5839
Page Range / eLocation ID:
216-224
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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