## Analyzing a robot arm that moves in 3D

In Robotics | No commentWe consider a robot with four joints that moves its end-effector in 3D space.

We consider a robot with four joints that moves its end-effector in 3D space.

We consider a robot with three joints that moves its end-effector on a plane.

We consider a robot, which has two rotary joints and an arm.

We consider the simplest possible robot, which has one rotary joint and an arm.

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

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.

This video gives summary of inertial sensors and navigation.

We learn the mathematical relationship between angular velocity of a body and the time derivative of the rotation matrix describing the orientation of that body.

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 learn the principles behind ‘gyros’, sensors that measure angular velocity with respect to the universe.

We learn how to use information from three magnetometers to determine the direction of the Earth’s north magnetic pole.

We learn the principles behind magnetometers, sensors that measure the Earth’s magnetic field.

We learn how to use information from three accelerometers to determine orientation.

We learn the principles behind accelerometers, sensors that measure acceleration due to motion and due to the Earth’s gravitational field.

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.

This video gives summary of paths and trajectories.

We combine what we’ve learnt about smoothly varying position and orientation to create smoothly varying pose, often called Cartesian interpolation.

We learn how to create smoothly varying orientation in 3D by interpolating Euler angles and Quaternions.

We learn to compute a trajectory that involves simultaneous smooth motion of many robot joints.

Frequently we want a trajectory that moves smoothly through a series of points without stopping.