MEMS sensors for assessing flow-related control of an underwater biomimetic robotic stingray

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(Zr(0.52)Ti(0.48))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.

Artificial fish skin of self-powered micro-electromechanical systems hair cells for sensing hydrodynamic flow phenomena

“…Unlike SU-8 processing that has been mainly used for hair cell fabrication in the past [22], m-SLA is a less cumbersome process that can form high-aspect-ratio pillars. m-SLA is micro-manufacturing process that allows building of three-dimensional microstructures directly from the model created by computer-aided design softwares [37]. It develops micro components by solidifying liquid monomer in a layer-by-layer fashion.…”

From Biological Cilia to Artificial Flow Sensors: Biomimetic Soft Polymer Nanosensors with High Sensing Performance

“…In most of the hair cell inspired flow sensors developed in the past, flow-generated deflection was transduced into an electrical output utilizing piezoresistive and piezoelectric sensing elements embedded in a MEMS cantilever or membrane 24 25 26 27 28 29 30 31 32 33 . Engineering a replication of the intricate morphological organization of the hair cell is a complex and challenging task.…”

“…Engineering a replication of the intricate morphological organization of the hair cell is a complex and challenging task. Therefore, in all the MEMS sensor developments, the basic MEMS sensor design followed a bio-inspired approach wherein; the ciliary bundle was approximated as a single cylindrical pillar deflected by flow 24 25 28 30 31 32 33 . Chen N. et al .…”

Hydrodynamic object identification with artificial neural models

“…Moreover, stealth technologies can render targets of interest invisible. To overcome these limitations, several recent attempts have been made to design artificial flow sensors by mimicking the basic principles of the LLS 4,[6][7][8][9][10] . Thanks to rapid developments in MEMS technology, hydrodynamic sensing could soon become a critical feature of autonomous surface and underwater vehicles performing navigation tasks in the marine environment.…”