Motion planning of continuum tubular robots based on features extracted from statistical atlas


Continuum tubular robots, which are constructed by telescoping pre-curved elastic tubes, are capable of balancing the force application and steerability during minimally invasive surgeries. These devices are able to reach the desired surgical sites in body cavities without colliding with critical blood vessels, nerves and tissues. However, the motion planning of continuum tubular robots is quite challenging because of their complicated kinematics as well as the high dimensional configuration space. In this paper, a sampling-based motion planning method is proposed based on the Rapidly-exploring Random Tree (RRT) algorithm for continuum tubular robots in 3D environments, such as medullary cavities. The proposed motion planner enables a continuum tubular robot to maneuver roughly along the central axis of the statistical humerus atlas in an approximate follow-the-leader manner. The experiment results have demonstrated the effectiveness and superiority of the proposed motion planning algorithm.

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