Fuzzy-RRT for Obstacle Avoidance in a 2-DOF Semi-Autonomous Surgical Robotic Arm

Kaaustaaub Shankar, Wilhelm Louw, Bharadwaj Dogga, Nick Ernest, Tim Arnett +1 more
4/24/2025
cs.ROcs.AI

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Abstract

AI-driven semi-autonomous robotic surgery is essential for addressing the medical challenges of long-duration interplanetary missions, where limited crew sizes and communication delays restrict traditional surgical approaches. Current robotic surgery systems require full surgeon control, demanding extensive expertise and limiting feasibility in space. We propose a novel adaptation of the Fuzzy Rapidly-exploring Random Tree algorithm for obstacle avoidance and collaborative control in a two-degree-of-freedom robotic arm modeled on the Miniaturized Robotic-Assisted surgical system. It was found that the Fuzzy Rapidly-exploring Random Tree algorithm resulted in an 743 percent improvement to path search time and 43 percent improvement to path cost.

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Cite this paper

@article{shankar2025fuzzyrrt,
  title  = {Fuzzy-RRT for Obstacle Avoidance in a 2-DOF Semi-Autonomous Surgical Robotic Arm},
  author = {Kaaustaaub Shankar and Wilhelm Louw and Bharadwaj Dogga and Nick Ernest and Tim Arnett and Kelly Cohen},
  year   = {2025},
  eprint = {2504.17979},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2504.17979v1}
}

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