HOW IT WORKS: Most robotic vehicles designed to navigate dangerous terrain rely on artificial vision or sonar systems to find the safest path. But robotic "eyes" don't operate well in low light and sonar can be confused by polished surfaces. The Johns Hopkins University scientists have turned to touch, inspired by how bugs use this sense to navigate dark rooms with varied surfaces. Just like a cockroach's antenna, the artificial version sends signals to the electronic brain of a wheeled robot, enabling the machine to scurry along walls, turn corners, and avoid obstacles in its path.
The antenna is made of cast urethane, a flexible substance that resembles rubber, encased in a clear plastic sheath. It contains six strain gauges, sensors that change resistance as they are bent. The device has been calibrated so that certain electric voltages correspond to certain bending angles as the antenna touches the wall or some other object. This data is fed to the robot's controller, enabling it to sense its position in relation to the way and to maneuver around obstacles. For instance, when the antenna signals that the robot is moving too close to a wall, the controller steers it away.
WHAT IS SWARM INTELLIGENCE: Building "swarms," of robotic insects that work together to adapt to their environment is part of "evolutionary robotics": creating machines that are digitally "bred" to evolve themselves. Swarm intelligence is the notion that complex behavior can arise from large numbers of individual agents each following very simple rules. For example, ants follow the strongest pheronome trail left by other ants to find the most efficient route to a food source, through a process of trial and error. A chunk of the plot in Michael Crichton's novel Prey was inspired in part by an experiment in which a fleet of robotic predators were programmed to seek out "prey" to get their next energy boost. The mechanical "prey," in contrast, were programmed to "graze" on special light sources and to keep alert for potential predators. The respective robots evolved increasingly complex hunting and escape strategies as the swarms of robots accumulated more and more data (in the form of experience) on which to base their decisions.
ON THE WEB: Johns Hopkins University Robotics Research