One of the main advantages to this type of actuation scheme is that compliance is built into the design, which provides a more fluid, varied movement for the camera, said Tom Secord, a former MIT colleague of Ueda's who is now an engineer at Medtronic, a biomedical device company in Minneapolis, Minn. He said:
What the cellular architecture shows you to do is activate small subgrounds to scale the output. By turning individual units on or off, which is very easy to do, you can achieve a wide range of outputs this simplifies the control problem of achieving a desired output for a robotic movement.
The end result is that we have a camera positioning mechanism that works in the same way as the human eye. The devices that drive it are flexible. They are stretchy like rubber bands in the same way the human eye muscles are.
While the mechanism is still being tested and there are no plans for commercial development yet, Schultz envisions several medical applications for the cellular actuation method used in the camera. The camera itself, for instance, could be used inside an MRI machine not only because of its movements but also because of its material composition. The mechanism created by Georgia Tech uses non-theritic materials that won't be affected by the procedure's magnetic field the way motors that use iron as their base would, Schultz said.
Traditional motors have iron-based materials and so they can't go in an MRI room [because] they will go flying into an MRI field and break the machine. Since the cellular actuators aren't made of iron, they are only minimally affected by the magnetic field. They may distort the image but it's not too bad. They can use the camera mechanism to look around in MRI [tests].
The cellular actuation method created by the team also opens the door for innovative new surgical devices that could complement the work of doctors by lending a robotic hand to their work, Schultz said.
This artificial muscle could be used... to apply a force to the patient, clamping a blood vessel, or pushing some tissue that's being operated on. This type of robotic actuation could be used to actuate a number of different surgical robotic devices.
While this is very interesting, one thing that the researchers did not address is a comparison of human motion and more traditional machine motion. While humans are very flexible, they are often not very precise. A more interesting question is what is the optimal type of motion.
I'm with you Naperlou. I would think there may be better vision models in nature than the human eye movement. The insect or bird worlds probably have superior versions of eye movement than human eye movement.
No matter which animal or human example you use, the Creator got it right the first time. It is a wise choice to not try and reinvent the wheel. It has already been invented! So, copy nature build a better mouse trap. The trick is to understand how He did it. That isn't so easy. There are reasons for everything nature does. Engineers need to take time and look around. It is amazing what the world has to teach us!
Yes, I am also fully agree with you both (Rob and Naperlou). In this case we can take the best example from nature i.e of a fish. If we consider the motion of fish eye its almost end to end from all directions and if this current invention matches with that then i feel that's the big acheivement.
I was actually thinking that there are a lot of weaknesses in trying to copy the motion the human eye. The two main things that popped into my mind was the relative lack of peripheral vision (compared with other animals) the the fact that it still needs to be mounted on a "neck" to see much of the field.
Acctually, it depends on what you are doing. The greatest advancement of science, wealth and welfare in history has come since the digital revolution. If you want to get philosophical, the universe is inherently mathematical. By applying digital techniques we have made tremendous advances. Frankly, there are lots of things we want done that are better done by computers than by natural methods. Nature tends to be very inefficient, using more resources to do a task than is strictly necessary. Natural language, for example, is terriably inefficient as far as information content.
Even in the area of accumulating and using knowledge, we have advanced more in the digital age, which encompasses the last sixty years or so, than in all of previous human history. I don't see this as "unnatural". We got here by using our natural talents and intelligence, but there is something about thinking digitally and mathematically that has given our knowledge a whole new dimension.
Good point, Asupnekar. There seems to be a proclivity to mimicking human movement and capabilities with robots. Yet other natural occurrences -- like your vision example of a fish -- are likely to be superior to human capabilities.
This is an interesting development, though it's helpful to understand that vision encompasse more than eye movement. There is the ability to accommodate wide variations in ambient light, to change focus on-the-fly smoothly, and to use the internal image-processing "firmware" of the brain to re-map conflicting or confusing imagery into a rational construct. Eyes are pretty amazing organs that must balance the interplay of a lot of variables to create what we call vision.
According to a study by the National Institute of Standards and Technology, one of the factors in the collapse of the original World Trade Center towers on Sept. 11, 2001, was the reduction in the yield strength of the steel reinforcement as a result of the high temperatures of the fire and the loss of thermal insulation.
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Robots are getting more agile and automation systems are becoming more complex. Yet the most impressive development in robotics and automation is increased intelligence. Machines in automation are increasingly able to analyze huge amounts of data. They are often able to see, speak, even imitate patterns of human thinking. Researchers at European Automation
call this deep learning.
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