A quaternion represents two things. It has an x, y, and z component, which represents the axis about which a rotation will occur. It also has a w component, which represents the amount of rotation which will occur about this axis. In short, a vector, and a float. With these four numbers, it is possible to build a matrix which will represent all the rotations perfectly, with no chance of gimbal lock. (I actually managed to encounter gimbal lock with quaternions when I was first coding them, but it was because I did something incorrectly. I'll cover that later). So far, quaternions should seem a lot like the axis angle representation. However, there are some large differences, which start....now.
What were the objective improvements ? ie. probability of detection vs false alarm rate ?
For some systems, such as the autonomous vehicle, sensor fusion is the key to the end result. Without it, the reaction is not what you want. Other aplications may provide an improvement in key sensor output and higher probablity of detection fewer false triggers. You do not want to do sensor fusion just for the sake of saying you used it in a product because there is a cost (development time for software and additional hardware) associated with sensor fusion.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
The IEEE Computer Society has named the top 10 trends for 2014. You can expect the convergence of cloud computing and mobile devices, advances in health care data and devices, as well as privacy issues in social media to make the headlines. And 3D printing came out of nowhere to make a big splash.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? Thats where the smart machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine whats possible with smart machines, and what tradeoffs need to be made to implement such a solution.