Search Results for: manipulability

The Jacobian matrix provides powerful diagnostics about how well the robot’s configuration is suited to the task. Wrist singularities can be easily detected and the concept of a velocity ellipse is extended to a 3-dimensional velocity ellipsoid.

We introduce serial-link robot manipulators, the sort of robot arms you might have seen working in factories doing tasks like welding, spray painting or material transfer. We will learn how we can compute the pose of the robot’s end-effector given knowledge of the robot’s joint angles and the dimensions of its links.

We summarise the important points from this masterclass.

Once a digital image exists as a matrix in the MATLAB workspace we can manipulate it to extract information that a robot could use. We will discuss some fundamental algorithms that operate on single images.

In a serial-link manipulator arm each joint has to support all the links between itself and the end of the robot. We introduce the recursive Newton-Euler algorithm which allows us to compute the joint torques given the robot joint positions, velocities and accelerations and the link inertial parameters.

A robot manipulator may have any number of joints. We look at how the shape of the Jacobian matrix changes depending on the number of joints of the robot.

We learn a method for succinctly describing the structure of a serial-link manipulator in terms of its Denavit-Hartenberg parameters, a widely used notation in robotics.

We consider the most general type of serial-link robot manipulator which has six joints and can position and orient its end-effector in 3D space.

We start by looking at a number of different types of robot arm with particular focus on serial-link robot manipulators.

We learn how to describe the orientation of an object by a 3×3 rotation matrix which has some special properties.