The research within the robotics area deals with various aspect of modeling and control of industrial robots. The research is to a large extent motivated by the challenge to keep or improve the robot performance while there is a continuously ongoing product cost reduction. The cost reduction results in more compliant robot structures with lower eigenfrequencies, higher friction, more nonlinear behavior, larger backlash, more complex vibration modes, and larger dynamic parameter variations between otherwise identical robots. The model-based control used today must therefore be further refined, for example to make it possible to adapt model parameters to the robot individuals and to take care of more complex robot dynamics. Today the robot arm control is based only on motor angle measurements and the control must rely on accurate dynamic models to control the arms of the robot. In applications with requirements on high robot control performance it will also be necessary to increase accuracy and robustness by introducing additional sensors in the arm system of the robot. Low-cost robots is not enough, the manufacturer must also guarantee a low life cycle cost. Improved diagnosis is then very important in order to be able to plan maintenance without disturbing the production. Accurate robot models are also needed for reliable diagnosis and the problems with increasing model complexity and larger model variations must be handled in the diagnosis case as well. Additional sensors will open up for improved tracking accuracy but also for more precise diagnosis functions.

The current activities concern

Identification

The cost reduction implies an increasing model complexity and larger model variations. This inherently requires effective methods to identify the unknown model parameters. Effective methods are particularly important since the parameter variations might require tuning of each individual robot.

Sensor fusion

Today, standard robot control is based only on sensors measuring the angles of the motor shafts. There is no measurement feedback from the arm structure, which is separated from the motor shafts by compliant bearings and compliant speed reducers with high friction and nonlinear stiffness. The aim of this project is to obtain better estimates of the robot tool position and orientation by adding sensors to the arm structure, for example accelerometers and gyroscopes.

Robot control

Results from the areas identification and sensor fusion can be used for improved control performance, and research topics of interest include Iterative Learning Control based on sensor fusion of motor measurements and arm sensors, robust feedback and feedforward control without additional sensors.

Diagnosis

Robotic-system faults are typically characterized by critical changes in the system parameters and can potentially result not only in the loss of productivity, but also in unsafe operation of the manipulator. Hence, automated monitoring - diagnostics - prognostics of the robotic manipulator and effective accommodation of such faults play a crucial role in the use of robotic manipulators as parts of an autonomous system.