While engineers have had success
building tiny, insect-like robots, programming them to behave autonomously like
real insects continues to present technical challenges. A group of Cornell
engineers has been experimenting with a new type of programming that mimics the
way an insect's brain works, which could soon have people wondering if that fly
on the wall is actually a fly. The amount of computer processing power needed
for a robot to sense a gust of wind, using tiny hair-like metal probes embedded
on its wings, adjust its flight accordingly, and plan its path as it attempts
to land on a swaying flower would require it to carry a desktop-size computer
on its back.
Unlike traditional chips that
process combinations of 0s and 1s as binary code, neuromorphic chips process
spikes of electrical current that fire in complex combinations, similar to how
neurons fire inside a brain. Researchers are developing a new class of event-based
sensing and control algorithms that mimic neural activity and can be
implemented on neuromorphic chips. Because the chips require significantly less
power than traditional processors, they allow engineers to pack more
computation into the same payload. They developed an 80-milligram flying
RoboBee outfitted with a number of vision, optical flow and motion sensors.
More information: