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arXiv AI By Tony Qin, Peter Connor, Khoa Dang, Carter Hatch, Caleb Rucker, Robert J. Webster III, Ron Alterovitz

Anatomy-Aware Dexterity-Driven Design Optimization of Surgical Continuum Robots

Read the original on arXiv AI →

The paper introduces a design optimization framework for surgical continuum robots that jointly considers dexterity and anatomical constraints. It defines the Reachable Volumetric Dexterous Solid Angle (RVDSA) as an objective metric, uses a computationally efficient motion planner to evaluate it, and applies an asymptotically optimal simulated annealing optimizer to find improved designs. Applying the method to a bimanual dexterous sheath robot for colon procedures yielded a 78% increase in RVDSA compared to optimization based solely on 3D voxel coverage.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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