Search Results for: depth estimation

We will extend our coverage of image processing. We will some previously discussed techniques in more depth, and introduce some additional ones.

We previously learnt how to derive a Jacobian which relates the velocity of a point, defined relative to one coordinate frame, to the velocity relative to a different coordinate frame. Now we extend that to the 3D case.

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 introduce resolved-rate motion control which is a classical Jacobian-based scheme for moving the end-effector at a specified velocity without having to compute inverse kinematics.

We will learn about inverse kinematics, that is, how to compute the robot’s joint angles given the desired pose of their end-effector and knowledge about the dimensions of its links. We will also learn about how to generate paths that lead to smooth coordinated motion of the end-effector.