Force control

By controlling the contact force, damage to the machine as well as to the objects to be processed and injuries when handling people can be prevented.

In manufacturing tasks, it can compensate for errors and reduce wear by maintaining a uniform contact force.

Force control is particularly suitable for contact tasks that serve to mechanically process workpieces, but it is also used in telemedicine, service robot and the scanning of surfaces.

For various reasons, movements of the robot or machine parts may be blocked by obstacles while the program is running.

If the trajectory is misaligned in classical motion control and thus it is not possible to approach the programmed robot pose(s), the motion control will increase the manipulated variable - usually the motor current - in order to correct the position error.

In mechanical manufacturing tasks, unevenness of the workpiece often leads to problems with motion control.

Force control (green) is useful here, as it ensures uniform material removal through constant contact with the workpiece.

This means in particular manufacturing tasks such as grinding, polishing and deburring as well as force-controlled processes such as controlled joining, bending and pressing of bolts into prefabricated bores.

Other applications of force control with potential contact can be found in medical technology and cooperating robots.

Robots used in telemedicine, i.e. robot-assisted medical operations, can avoid injuries more effectively via force control.

Here, force control helps to deal with obstacles and deviations in the environmental model and to avoid damage.

The first important work on force control was published in 1980 by John Kenneth Salisbury at Stanford University.

In addition to the widely used strain gauges made of variable electrical resistances, there are also other versions that use piezoelectric, optical or capacitive principles for measurement.

To exclude temperature influences and increase measurement reliability, two strain gauges can be arranged in a complementary manner.

These are mounted between the robot hand and the end effector and can record both forces and torques in all three spatial directions.

Since force/torque sensors are still relatively expensive (between €4,000 and €15,000) and very sensitive to overloads and disturbances, they - and thus force control - have been reluctantly used in industry.

In addition to cost savings, dispensing with these sensors has other advantages: Force sensors are usually the weakest link in the mechanical chain of the machine or robot system, so dispensing with them brings greater stability and less susceptibility to mechanical faults.

Adjusted for gravitational, inertial and frictional effects, the motor currents are largely linear to the torques of the individual axes.

Compliance is defined in the literature as a "measure of the robot's ability to counteract contact forces."

Here, the compliance of the robot system is modeled as mechanical impedance, which describes the relationship between applied force and resulting velocity.

Here, the robot's machine or manipulator is considered as a mechanical resistance with positional constraints imposed by the environment.

Instead, the manipulator and/or end effector is flexibly designed in a way that can minimize contact forces that occur during the task to be performed.

The figure opposite shows a so-called Remote Center of Compliance (RCC) that makes this possible.

As shown in the following figure, a corresponding infeed correction is calculated from the difference between the nominal and actual force.

)has a higher priority, i.e. a position error is tolerated in favor of the correct force control.

[12] In this case, the inner control loop should have a saturation in order not to generate a (theoretically) arbitrarily increasing velocity in the free movement until contact is made.

Force and position control is then explicitly specified for each spatial direction; the matrix Σ is then static.

The previously mentioned, non-adaptive concepts are based on an exact knowledge of the dynamic process parameters.

Adaptive control is therefore usually first used offline and the results are intensively tested in simulation before being used on the real system.

Accordingly, concepts from force and impedance control are specifically used in this area to increase safety, as this allows the robot to interact with the environment and humans in a compliant manner.