Search Results for: acceleration

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

We describe inertia of the robot as a matrix which represents how inertia of a joint depends on the position of all the joints, and how the torque on one joint depends on the acceleration of other joints.

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.

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

A number of strategies exist to reduce the effect of these coupling torques between the joints, from introducing a gearbox between the motor and the joint, to advanced feedforward strategies.

A more efficient trajectory has a trapezoidal velocity profile.

The simplest smooth trajectory is a polynomial with boundary conditions on position, velocity and acceleration.

We summarise the important points from this lecture.

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

All animals have a variety of senses that help them in everyday life. We’ll talk about interesting non-human senses that some animals possess and the often overlooked human sense of balance which is based on accelerometers and gyroscopes in our vestibular system.