Soft Array Surface-Changing Compound Eye

Abstract

The field-of-view (FOV) of compound eyes is an important index for performance evaluation. Most artificial compound eyes are optical, fabricated by imitating insect compound eyes with a fixed FOV that is difficult to adjust over a wide range. The compound eye is of great significance in the field of tracking high-speed moving objects. However, the tracking ability of a compound eye is often limited by its own FOV size and the reaction speed of the rudder unit matched with the compound eye, so that the compound eye cannot better adapt to tracking high-speed moving objects. Inspired by the eyes of many organisms, we propose a soft-array, surface-changing compound eye (SASCE). Taking soft aerodynamic models (SAM) as the carrier and an infrared sensor as the load, the basic model of the variable structure infrared compound eye (VSICE) is established using an array of infrared sensors on the carrier. The VSICE model is driven by air pressure to change the array surface of the infrared sensor. Then, the spatial position of each sensor and its viewing area are changed and, finally, the FOV of the compound eye is changed. Simultaneously, to validate the theory, we measured the air pressure, spatial sensor position, and the FOV of the compound eye. When compared with the current compound eye, the proposed one has a wider adjustable FOV.

Keywords: artificial compound eye; infrared sensor array; pneumatic; soft.

Figure 1

(a) The eight-eyed jumping spider with an annular compound eye structure has a 360° FOV; (b) Squid eyes with the ability to change their FOV. (c) Insect compound eye capable of detecting high-speed objects.

Figure 2

The soft array surface changes the basic structure of the compound eye. (a) Top view of unfilled gas; (b) Oblique view of unfilled gas; (c) Top view of filled gas; (d) Oblique view of filled gas.

Figure 3

(a) SASCE is the FOV of the plane; (b) SASCE is the FOV of the surface.

Figure 4

Based on the ABAQUS software, the model state renderings of the CTPM under different air pressures are simulated. (a–f) is the simulation effect diagram of CTPM from the relative ambient air pressure 6 kPa–36 kPa with a gradient of 6 kPa.

Figure 5

The ABAQUS software simulates the model state effect diagram of SAM under different air pressures. (a–f) is the simulation effect diagram of the SAM from relative ambient air pressure 6 kPa–36 kPa with a gradient of 6 kPa.

Figure 6

Relationship between the distance from the central axis of the model (the horizontal position relative to the ambient air pressure of 0 Pa) and the horizontal displacement under different air pressures. SI represents the relationship between the distance of the CTPM from the central axis and displacement under different air pressures. SII represents the relationship between SAM’s maximum constraint, that is, the distance between each point on the line constrained by three sensors and passing through the central axis, and the horizontal displacement. SIII represents the relationship between SAM’s minimum constraint, that is, the distance between each point on the line constrained by only one sensor in the center and passing through the central axis, and the horizontal displacement.

Figure 7

Outline drawing under different air pressures. OCI represents the outline of CTPM under different air pressures; OCII represents the contour of the line where SAM is constrained the most, that is, it is constrained by three sensors and passing through the central axis; OCIII represents the contour of the line whose SAM is constrained the least, that is, it is constrained by only one sensor in the center and passing through the central axis.

Figure 8

Relationship between the distance from the central axis (the distance relative to the ambient air pressure of 0 Pa) and the thickness change under different air pressures. δI represents the thickness variation law of a circular thin plate; δII represents the thickness variation law of the soft pneumatic compound eye model with the maximum constraint; that is, it is constrained by three sensors and passing through the central axis; δIII represents the thickness variation law of the soft pneumatic compound eye model with the least constraint; that is, it is constrained by only one sensor, located in the center and passing through the central axis.

Figure 9

SAM mold preparation.

Figure 10

SAM main body production.

Figure 11

Sam group transfer.

Figure 12

Double-layer structure design and manufacturing of the mold and CTPM manufacture mold. (a) Design mold for double-layer structure; (b) Mold for CTPM.

Figure 13

Architecture of the VSICE system: seven infrared array sensors are attached to the SAM, the outer membrane controls the internal air pressure of the SAM through an air pump to change the array surface, and the infrared array sensors are directly connected to Arduino. Data are transmitted in real time through IIC to the computer for processing.

Figure 14

VSICE model. (a) The VSICE in the initial state is in the plane compound eye mode. (b) The shape of the VSICE in the inflated state is a curved compound eye mode.

Figure 15

CTPM experimental diagram. (a–f) respectively represent the state record diagram of the circular thin plate model with 6 kPA–36 kPa pressure increasing at an interval of 6 kPa.

Figure 16

SAM experimental diagram, (a–f) represent the state recording diagram of the soft pneumatic compound eye model at 6 kPa–36 kPa increasing at an interval of 6 kPa.

Figure 17

FEA and actual contour of the CTPM under different various air pressure values. The solid line represents the results of FEA based on ABAQUS, and the dotted line represents the actual measurement results.

Figure 18

Relationship between CTPM and SAM center point displacement and air pressure. (a) Relationship between CTPM center point displacement and air pressure and (b) relationship between SAM center point displacement and air pressure. Experimental data represent the relationship between center point displacement measured by the model and air pressure. FEA represents the relationship between center point displacement and air pressure based on the ABAQUS finite-element analysis. Mathematical model, which models data into Equations (5)–(8), represents the relationship between the displacement of the center point and the air pressure.

Figure 19

Horizontal distance–vertical displacement and air pressure–horizontal distance diagrams of the outer ring points (attachment point of SAM’s outer ring sensor and the corresponding point of CTPM’s outer ring sensor attachment point). (a,b) represent the outer ring point displacement path curves of CTPM and SAM, respectively, where experimental data represent the measured point displacement results, and FEA represents the simulated point displacement path curve. The simulation curve represents the curve fitted according to the actual measurement points. (c) represents the pressure level position relationship curve obtained from CTPM and SAM finite-element analysis.

Figure 20

Schematic diagram of the test VSICE experimental platform.

Figure 21

Schematic diagram of the FOV experiment. (a) The steering gear pan tilt was used to level the center sensor. (b) Using a rotation angle of $${\phi }_i$$ for the steering gear pan tilt, the heat source was imaged at the edge of the FOV.

Figure 22

VSICE FOV curve, where V is half the FOV of VSICE.

Figure 23

FOV test at 0 Pa; (a) Compound eye front test image. (b) An image in which the compound eye is rotated to the edge of the FOV.

Figure 24

FOV test at 18 kPa. (a) Front test image of the compound eye. (b) Test image of the edge position of the compound eye rotation field.

Figure 25

FOV test at 36 kPa. (a) Front test image of compound eye. (b) Test image of the compound eye rotated to the edge of the FOV.