Search Results for: IMU

The image Jacobian depends not only on the image plane coordinates but also the distance from the camera to the points of interest. If this distance is not known, what can we do? Let’s look at how we can determine this distance, and how the optical flow equation can be rearranged to convert from observed […]

The relationship between world coordinates, image coordinates and camera spatial velocity has some interesting ramifications. Some very different camera motions cause identical motion of points in the image, and some camera motions leads to no change in the image at all in some parts of the image. Let’s explore at these phenomena and how we […]

We learn how accelerometers and gyroscopes can be combined into an inertial navigation system capable of estimating position and orientation of a vehicle, without GPS.

We will learn the essentials of inertial navigation, about sensors such as accelerometers, gyroscopes and magnetometers and how we can use the information they provide to estimate our motion and orientation in 3D space.

We will use Simulink to create a dynamic model of a single robot joint and simulate its operation.

We use MATLAB and some Toolbox functions to model the spectrum of a realistic light source, its modification after reflection from a colored object and the response of the cone cells to form a tristimulus response.

Actuators have finite capability, that is they have a maximum torque, velocity and power rating.

So far we have worked out the torques on a robot’s joints based on joint position, velocity and acceleration. For simulation we want the opposite, to know its motion given the torques applied to the joints. This is called the forward dynamics problem.

So far we have taken a linear combination of pixels in the box around the input pixel, but non-linear operations like sorting and ranking the pixel values also prove to be very useful. We look at the median filter which is much better at removing salt and pepper noise from image than simple smoothing.

We start by considering the effect of gravity acting on a robot arm, and how the torque exerted will disturb the position of the robot controller leading to a steady state error. Then we discuss a number of strategies to reduce this error.