Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities
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Robotic assistance allows surgeons to perform dexterous and tremor-free procedures, but robotic aid is still underrepresented in procedures with constrained workspaces, such as deep brain neurosurgery and endonasal surgery. In those, surgeons have restricted vision to areas near the surgical tool tips, which increases the risk of unexpected collisions between the shafts of the instruments and their surroundings, in special when those parts are outside the surgical field-of-view. Dynamic active constraints can be used to prevent collisions between moving instruments and prevent damage to static or moving tissues. In this work, our vector field inequality method is extended to provide dynamic active constraints to any number of robots and moving objects sharing the same workspace. The method is evaluated in experiments and simulations in which the robot tools have to avoid collisions, autonomously and in real-time, with a constrained endonasal surgical environment and between each other. Results show that both manipulator-manipulator and manipulator-boundary collisions can be effectively prevented using the vector field inequalities.
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