External force estimation during compliant robot manipulation

This paper presents a method to estimate external forces exerted on a manipulator during motion, avoiding the use of a sensor. The method is based on task-oriented dynamics model learning and a robust disturbance state observer. The combination of both leads to an efficient torque observer that can be incorporated to any control scheme. The use of a learning-based approach avoids the need of analytical models of joints' friction or Coriolis dynamics effects.

Authors

• Adrià Colomé
• Diego Pardo
• Guillem Alenyà
• Carme Torras

Keywords

• Robots
• Force
• Observers
• Joints
• Friction
• Acceleration
• External Force
• Force Estimation
• Robot Manipulator
• Compliant Robot
• External Force Estimation
• Control Strategy
• Dynamic Model
• State Observer
• Use Of Sensors
• Estimation Error
• Large Errors
• Position Error
• Inverse Model
• Joint Position
• Proportional-integral-derivative
• Error Dynamics
• Robot Motion
• Inverse Dynamics
• Inertia Matrix
• Joint Velocity
• External Torque
• Expensive Sensors
• Static Friction
• Global Learning
• Position Estimation Error
• Disturbance Observer
• Joint Acceleration
• Disturbance Estimation
• Acceleration Measurements
• Position Estimation