Learning force control with position controlled robots

The paper applies a previously presented method for accurate tracking of paths to force control. This approach is very simple since it does not require a joint torque/motor current interface but only a positional interface. It can be applied with elastic end-effectors (sensors) as well as with stiff environments where most elasticity is in the robot joints. In both cases deviations from the desired forces are transferred to positional deviations on joint level. The resulting path can then be controlled with high accuracy by a learned feedforward controller including the influence of the forces. The approach can be applied to the sensing of a contour or to the tracking of a known contour with high speed.

Authors

• Friedrich Lange
• Gerhard Hirzinger

Keywords

• Force control
• Robot control
• Force sensors
• Robot sensing systems
• Robot kinematics
• Sampling methods
• Control systems
• Torque
• Orbital robotics
• Shape
• Positive Control
• Learning Control
• Feedforward Control
• Joint Torque
• Feedback Control
• Direct Control
• Sensory Signals
• Path Planning
• Joint Angles
• Error Reduction
• Contact Force
• Error Control
• Force Sensor
• End-effector
• Force Vector
• Neural Net
• Laser Ranging
• Sampling Instants
• Force Error
• Contour Shape
• Torque Sensor