MEMS sensors for assessing flow-related control of an underwater biomimetic robotic stingray. (18th May 2015)

• Record Type: Journal Article
• Authors: Asadnia, Mohsen; Kottapalli, Ajay Giri Prakash; Haghighi, Reza; Cloitre, Audren; Alvarado, Pablo Valdivia y; Miao, Jianmin; Triantafyllou, Michael
• Is Part Of: Bioinspiration & biomimetics. Volume 10:Number 3(2015:Jun.)
• Publication Date: 2015-05-18
• Subjects: biomimetics -- underwater sensing -- underwater robotic vehicles -- MEMS pressure/flow sensors -- model predictive control; Biomimetics -- Periodicals; Biomedical materials -- Periodicals; Medical innovations -- Periodicals; Biomedical engineering -- Periodicals; 600
• DOI: 10.1088/1748-3190/10/3/036008
• Languages: English
• ISSNs: 1748-3182

Abstract

Abstract: A major difference between manmade underwater robotic vehicles (URVs) and undersea animals is the dense arrays of sensors on the body of the latter which enable them to execute extreme control of their limbs and demonstrate super-maneuverability. There is a high demand for miniaturized, low-powered, lightweight and robust sensors that can perform sensing on URVs to improve their control and maneuverability. In this paper, we present the design, fabrication and experimental testing of two types of microelectromechanical systems (MEMS) sensors that benefit the situational awareness and control of a robotic stingray. The first one is a piezoresistive liquid crystal polymer haircell flow sensor which is employed to determine the velocity of propagation of the stingray. The second one is Pb(Zr0.52 Ti0.48 )O3 piezoelectric micro-diaphragm pressure sensor which measures various flapping parameters of the stingray's fins that are key parameters to control the robot locomotion. The polymer flow sensors determine that by increasing the flapping frequency of the fins from 0.5 to 3 Hz the average velocity of the stingray increases from 0.05 to 0.4 BL s −1, respectively. The role of these sensors in detecting errors in control and functioning of the actuators in performing tasks like flapping at a desired amplitude and frequency, swimming at a desired velocity and direction are quantified. The proposed sensors are also used to provide inputs for a model predictive control which allows the robot to track a desired trajectory. Although a robotic stingray is used as a platform to emphasize the role of the MEMS sensors, the applications can be extended to most URVs.