Robot With Broken Leg Learns To Walk Again In Under 2 Minutes 69
KentuckyFC (1144503) writes When animals lose a limb, they learn to hobble remarkably quickly. And yet when robots damage a leg, they become completely incapacitated. That now looks set to the change thanks to a group of robotics engineers who have worked out how to dramatically accelerate the process of learning to walk again when a limb has become damaged. They've tested it on a hexapod robot which finds an efficient new gait in under two minutes (with video), and often faster, when a leg becomes damaged. The problem for robots is that the parameter space of potential gaits is vast. For a robot with six legs and 18 motors, the task of finding an efficient new gait boils down to a search through 36-dimensional space. That's why it usually takes so long. The new approach gets around this by doing much of this calculation in advance, before the robot gets injured. The solutions are then ordered according to the amount of time each leg remains in contact with the ground. That reduces the dimension of the problem from 36 to 6 and so makes it much easier for the robot to search. When a leg becomes damaged, the robot selects new gaits from those that minimize contact with the ground for the damaged limb. It compares several and then chooses the fastest. Voila! The resulting gaits are often innovative, for example, with the robot moving by springing forward. The new approach even found a solution should all the legs become damaged. In that case, the robot flips onto its back and inches forward on its "shoulders."
Controlling Damaged Aircraft (Score:5, Informative)
I recall about a decade ago the Department of Defense or NASA working on this sort of adaptability for controlling damaged aircraft.
An aircraft that suddenly loses use of a part of a wing or a flight control surface may still have sufficient flight control capability to fly home. The problem generally is that the pilot's control inputs won't produce the same motion responses, and the pilot generally has only seconds to map the inputs to control outputs.
The idea was for the computer to do this mapping for the pilot, so the pilot would continue to apply the appropriate inputs (to roll the plane for example). The computer would determine which of the remaining flight surfaces to employ in order to best achieve the desired motion.
One example that I recall was when the aircraft rudder was lost, yaw motion was compensated by dropping the landing gear and speed brakes on only one side of the aircraft to cause more drag on only one side, yawing the aircraft.