One of the reasons we don't yet have self-driving cars and mini-helicopters delivering online purchases is that autonomous vehicles tend not to perform well under pressure. A system that can flawlessly parallel park at 5 mph may have trouble avoiding obstacles at 35 mph.
Part of the problem is the time it takes to produce and interpret camera data. An autonomous vehicle using a standard camera to monitor its surroundings might take about a fifth of a second to update its location. That's good enough for normal operating conditions but not nearly fast enough to handle the unexpected.
At this year's International Conference on Robotics and Automation, Andrea Censi and Davide Scaramuzza of the University of Zurich present the first state-estimation algorithm—the type of algorithm robots use to gauge their position—to process data from event-based sensors. A robot running their algorithm could update its location every thousandth of a second or so, allowing it to perform much more nimble maneuvers. Read entire article here>