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With the potential applications of capsule robots in medical endoscopy,accurate dynamic control of the capsule robot is becoming more and moreimportant. In the scale of a capsule robot, the friction between capsule andthe environment plays an essential role in the dynamic model, which is usuallydifficult to model beforehand. In the paper, a tethered capsule robot systemdriven by a robot manipulator is built, where a strong magnetic Halbach arrayis mounted on the robot's end-effector to adjust the state of the capsule. Toincrease the control accuracy, the friction between capsule and the environmentis learned with demonstrated trajectories. With the learned friction model,experimental results demonstrate an improvement of 5.6% in terms of trackingerror.

Learning Friction Model for Tethered Capsule Robot