Surgical Tool Path Updating for Manual-to-Robotic Tissue Removal
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Solution Overview
Problem
Current robotic surgical systems face challenges in seamlessly switching between semi-autonomous and manual modes during procedures, limiting the ability to adapt to changing conditions such as unexpected tissue movement or instrument collisions, which can lead to inefficiencies and increased risk of errors.
Innovation Solution
A surgical system comprising a manipulator, a tool path generator, a material logger, and a controller that allows for real-time switching between manual and semi-autonomous modes by monitoring the surgical instrument's movement, updating the solid body model of the surgical site, and modifying the tool path to account for applied material, enabling precise control and adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robotic system operates in semi-autonomous mode with preprogrammed paths, then positioning precision is improved, but adaptability to unexpected conditions deteriorates
Solution Approach 1:
The robotic system implements dynamic mode switching capability, allowing transition between semi-autonomous mode (for high precision positioning along preprogrammed paths) and manual mode (for adaptability to unexpected conditions). This resolves the contradiction by making the system's control characteristics changeable rather than fixed, enabling the practitioner to select the appropriate mode based on real-time surgical conditions
2Adaptability or versatility
If the robotic system operates in manual mode with practitioner control, then adaptability to changing conditions is improved, but positioning precision deteriorates
Solution Approach 1:
The system allows dynamic switching between manual mode (providing adaptability through direct practitioner control) and semi-autonomous mode (providing high positioning precision through robotic control along preprogrammed paths). This resolves the contradiction by enabling the practitioner to use manual control for adaptability when needed while relying on automated precision control during stable phases
3Productivity
If the robotic system uses preprogrammed paths for material removal, then procedural efficiency is improved, but ability to account for actual tissue conditions deteriorates
Solution Approach 1:
The system implements dynamic mode switching between semi-autonomous operation with preprogrammed paths (for procedural efficiency) and manual control mode (for adapting to actual tissue conditions). This allows the practitioner to efficiently remove material along predetermined paths when conditions are stable, then switch to manual control when unexpected tissue variations require adaptation
Solution Approach 2:
The system incorporates feedback mechanisms that allow the practitioner to monitor the robotic system's operation and switch modes based on observed tissue conditions. This feedback loop enables the system to account for actual tissue conditions by allowing manual intervention when the preprogrammed path no longer matches the actual surgical reality
Data Source
AI summary
A tool path generator utilizes a solid body model of a volume to generate a tool path for a manipulator to remove material of the volume with an energy applicator in a semi-autonomous mode. A material logger monitors movement of the energy applicator according to a cutting path taken by a practitioner in the manual mode, identifies material of the volume to which the energy applicator has been applied in the manual mode, and updates the solid body model based on the identified material. The tool path generator modifies the tool path based on the updated solid body model such that, for the semi-autonomous mode, the modified tool path accounts for the identified material of the volume to which the energy applicator has been applied in the manual mode.