A Fish Out of Water

Everything from robots to virtual and augmented reality headsets need to get their bearings by examining the objects around them before they can be of much use. Most commonly, this is done by using cameras in conjunction with machine learning algorithms that were developed to recognize objects that are of interest for a given application. These sorts of methods have proven themselves to be extremely effective, yet the cameras and computing equipment that is powerful enough to run the algorithms tends to be bulky, fiddly, and energy-hungry.

These characteristics are unsuitable for many applications, especially when it comes to portable and wearable devices. As such, researchers are always on the lookout for more efficient ways for artificial systems to sense objects in their surroundings. Recently, a team led by researchers at the City University of Hong Kong drew inspiration from an unlikely source — fish. In particular, they took a look at the elephantfish, which is native to Africa. These fish generate a weak electric field which they use to sense nearby prey, even in murky water that blocks vision.

The team took a closer look at the specialized organs of the elephantfish that give them this unique capability. In doing so, they realized that they could reproduce the functionality in a way that would be far more efficient — in terms of energy consumption and processing requirements — than a computer vision-based system. That led them to build an electronic skin that is capable of non-contact three-dimensional tracking and sensing of nearby objects, regardless of their conductivity.

The design of the electronic skin incorporates several layers, including a transmitter and a receiver layer, which work together to detect objects in three-dimensional space. The transmitter generates an electrical field that extends beyond the sensor’s surface, while the receiver detects disruptions in this field caused by nearby objects. By arranging the sensing components in a grid, it is possible to determine the distance and direction of objects.

A separate controller connected via wires powers the system, generates the driving signal for the transmitter, and processes the data from the receiver using 16-bit analog-to-digital converters. A microcontroller computes the target’s position and transmits this information wirelessly to a smartphone or other device using Bluetooth Low Energy. The entire system is powered by a rechargeable lithium-ion battery.

Much like a fish out of water, this system is a bit clumsy when taken out of its natural environment. It can detect objects up to 1 meter away underwater, but is limited to about 10 centimeters in open air. The sensor is also limited in the sizes of objects it can detect — it is optimized to recognize objects that are around 8 mm in diameter. Both smaller and larger objects pose problems for the sensor. Furthermore, environmental factors, such as humidity and electromagnetic interference, can also affect its accuracy.

These significant limitations will undoubtedly restrict the applications that this technology can be used for at present. If the researchers can overcome these limitations, this innovation might hold promise for future developments in human-machine interfaces, wearable sensors, and flexible electronic skin systems.