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In this work, a passive physical human-robot interaction (pHRI) controller is proposed to intraoperatively ensure that sensitive tissues will not be damaged by the robot's tool. The proposed scheme uses the point cloud of the restricted region's surface as constraint definition and Artificial Potential fields for constraint enforcement. The controller is proven to be passive with respect to the interaction force and to guarantee constraint satisfaction in all cases. The proposed methodology is experimentally validated by the kinesthetic guidance of a KUKA LWR4+ robot's end-effector driving a virtual slave KUKA in the vicinity of a 3D point-cloud of a kidney and its adjacent vessels.

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SUMMARYThe progressive automation framework allows the seamless transition of a robot from kinesthetic guidance to autonomous operation mode during programming by demonstration of discrete motion tasks. This is achieved by the synergetic action of dynamic movement primitives (DMPs), virtual fixtures, and variable impedance control. The proposed DMPs encode the demonstrated trajectory and synchronize with the current demonstration from the user so that the reference generated motion follows the human’s demonstration. The proposed virtual fixtures assist the user in repeating the learned kinematic behavior but allow penetration so that the user can make modifications to the learned trajectory if needed. The tracking error in combination with the interaction forces and torques is used by a variable stiffness strategy to adjust the progressive automation level and transition the leading role between the human and the robot. An energy tank approach is utilized to apply the designed controller and to prove the passivity of the overall control method. An experimental evaluation of the proposed framework is presented for a pick and place task and results show that the transition to autonomous mode is achieved in few demonstrations.