Kinematic control

Often the systems are composed of a floating base or a ground base and one or more joint chains attached. During my research activity, I worked on two floating base systems, an underwater system with a six-joint manipulator fixed to the base; for the aerial field, I worked on a quadrotor and multirotor with one or more manipulators attached.

When the system is composed of many joints, determining each joint position at any time to have a precise place of the end joint is not a simple task. 

Imagine taking an object from the table and putting it in the sink. Our brain makes some operations to determine every single art position, to make the operation. A robot with kinematic control computes each joint position to bring the end joint to the desired position. Where the end joint wanted position is the motion planning result.

Most of the time, the kinematic control uses the kinematic inversion, then starting from the end joint desired position, the control makes the inverse computation to have each joint position. The kinematic inversion uses the Jacobian, which is a matrix. Through the Jacobian inversion, we can have the joint desired velocity; we obtain the desired position by integrating the rate.

The kinematic control does not compute only the position; we can add multiple tasks to the control. We have many tasks; some of them can be energy efficiency or obstacle avoidance. We can add as many tasks as many degrees of freedom we have.

In this post, I introduced kinematic control. For a more thorough description, I suggest visiting my research page, or you can see my Google Scholar profile.

It is a pleasure to see you here at this article end, and I’m delighted if you need don’t hesitate to contact me, for any motivation at the following mail.