Orientation maps speed robotic needle entry point planning
Compressed Orientation Reachability Maps for Sub-Second Robotic Needle Entry Point Planning
RoboticsComputational Geometry
Summary
Planning where a robot can safely insert a needle into the liver during surgery takes a lot of time, slowing down the process. The authors created a special map that shows which needle angles and positions work for the robot without having to recalculate each time. This map is stored in a small, easy-to-access file, letting the robot find a good entry point very quickly. Their tests showed it speeds up planning from over 13 seconds to less than half a second, helping surgeries happen faster and more smoothly.
What this means in practice
- •For robotics engineers: integrate rapid orientation reachability maps to cut needle entry planning times in robotic surgical systems by over 90%
- •For medical device teams: develop minimally invasive liver intervention tools that enable sub-second entry point computation for intraoperative needle guidance$Commercial implications: This paper enables real-time needle trajectory planning software valuable to companies making robotic surgery devices.
Authors
Prabhu Nithin Gollapudi, Andreas Maier, Franziska Mathis-Ullrich, Water Zhao, Jia Wang, Siming Bayer
Abstract
In the context of multi-stage trajectory planning for robotic percutaneous liver interventions, identifying a kinematically feasible entry point remains a critical computational bottleneck. Existing methods rely on exhaustive inverse kinematics or randomized searches, incurring delays of 13 to 27 seconds per target and limiting real-time intraoperative adaptation. This paper introduces an Orientation-Based Reachability Map (ORM) that precomputes the kinematic feasibility of a 6 Degrees of Freedom (DoF) serial manipulator across 188,873 workspace positions and encodes orientation feasibility into a compact, indexed 83 MB map. A Just-In-Time (JIT) compiled runtime pipeline replaces live optimization with near-instantaneous array lookups. Experimental evaluation demonstrates a reduction in planning latency from 13.5-26.9 s to 0.289-0.349 s per target while maintaining high geometric fidelity, achieving a mean convex hull volume overlap ratio of 0.933 and a mean alpha-shape volume ratio of 0.976 relative to the baseline reachable point cloud. The proposed ORM framework enables sub-second entry point planning and provides an efficient computational framework for robotic needle insertion in percutaneous liver ablation.