Currently robots need to be precisely programmed for each step of a given task, but the move towards autonomous systems will see robots reacting intelligently to their surroundings and performing tasks largely independently. To do this they will need to rely on their own sensory perceptions. However, in harsh environments, laid low by fumes, dust, water, high temperatures or low visibility, new senses are called for – perhaps even sensory organs that humans lack. Researchers have fitted an underwater robot with an artificial sensory organ inspired by the so-called lateral line system found in fish and some amphibians that lets it orient itself in murky waters.
Non-existent in land animals, the lateral line is a sense organ used to detect movement and vibration in the surrounding water. This organ extends along both sides of the body and allows the aquatic organism to form a very detailed picture of their immediate surroundings at a range of about the length of their body, even in murky water. The researchers expect giving such capabilities to underwater robots will enable them to work autonomously in operations ranging from deep-sea exploration to inspection of sewer pipes.
In nature the lateral lines are composed of hundreds or even thousands of fine sensory hairs that are located in tiny ducts beneath the skin and that register even tiny changes in flow velocity. In terms of precision, these sensors are comparable with the human inner ear, where hundreds of thousands of fine sensory hairs enable us to distinguish between sounds.
To develop lateral line system for their underwater robot “Snookie,” a team from Germany’s Technische Universitaet Muenchen (TUM) created an artificial organ that measures changes in pressure and flow around the robot not with conventional dynamic indicators, which would be far too large and imprecise, but with thermistors.
When a change in flow velocity occurs, this immediately causes a change in the heat dispersed through a heated wire. This in turn can be measured electronically by the sensor elements with great speed, and in a minimum of space. At intervals of a tenth of a second and using only a tiny amount of electrical energy, the sensors register pressure fluctuations of less than one percent over an area of just a few square millimeters.
However, the complicated part is not the sensor itself, but how the signals it sends are processed to create a complete picture of the surrounding area. Differences in pressure are much more difficult to accurately pin down than waves of light. The system relies on analyzing the tiniest differences in timing of the pressure fluctuations to detect its surroundings, which is why the speed of the sensors is so important. The system allows Snookie to detect obstacles and movements in the water a hand's breadth in front of its nose and on either side.
Snookie – named after a species of perch with a distinctive lateral line – is a robot fish made of Plexiglas and aluminum, about 80 centimeters long and 30 centimeters in diameter, stuffed to the gills with an electronic control system and a power supply. Among its striking external features are six propeller gondolas that drive and position the robot, and a yellow hemispherical nose to which the sensors that guide the underwater vehicle are secured.
The TUM scientists chose an underwater vehicle to test their technology because it presented a set of challenges not experienced by autonomous robots on land. Visibility underwater is often limited to just a few centimeters and the infrared detectors commonly used by land robots alongside cameras to identify their surroundings do not work underwater. Also wireless communication is restricted underwater, as are energy supplies.
"An underwater robot is as much on its own as a vehicle on Mars," says electrical engineer Stefan Sosnowski who works in the Department of Robotics headed by Professor Sandra Hirche and is responsible for the design of the underwater craft. His colleague, biophysicist Dr. Jan-Moritz Franosch, aided by a group of students, developed the artificial lateral line for the robot.
The scientists look on Snookie as more than just an experiment. They expect autonomous underwater robots to find a broad range of applications - from investigating shipwrecks to carrying out deep-sea search missions, for example to locate the flight recorder after air disasters. More mundanely, they could also be used to inspect tanks and sewer pipes.
They also expect that robots with even more sensitive lateral line systems will have considerable potential uses on land, as it is of course equally possible to detect variations in pressure and flow in air, as well as water. Another external project is working on this subject.
Man-made lateral lines might for example offer a cheaper alternative to the laser scanners currently used by robots to feel their way about their immediate surroundings – with the advantage that, unlike laser scanners, lateral lines won't be blinded by other robots. This would allow autonomous robots to be deployed in swarms, opening the way for entirely new applications.
Biophysicist Prof. van Hemmen has more on his mind than just autonomous underwater robots. His goal is to develop and combine new forms of technological sensory perception, as he is convinced that in this way machines can perceive their environment with much greater accuracy. "The key here is 'multimodal sensing,'" he explains. "Humans, too, don't rely on a single sense. Our brains combine the input from a variety of senses to create an overall image of our surroundings. It is not until one of our senses fails us that we appreciate how important this combination is."
Van Hemmen is also convinced that robot intelligence benefits little from installing even more cameras to supply even more images. He believes that it is more important for robots to perceive different aspects of their environment with a variety of sensors.
The TUM team is part of the CoTeSys research cluster that brings together around 100 scientists working in widely differing fields at five universities and research institutes in the Munich area, in the interest of developing better cognitive capabilities for technical systems. The goal is to make robots more self-sufficient, able to analyze for themselves and flexibly respond to the situations in which they find themselves - from recognizing their surroundings through to independently performing their allotted tasks.