Medical Robotic Arm Configuration Optimization

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Solution Overview

Problem

Medical robotic arms face challenges in reaching all positions within their workspace, especially when carrying heavy loads or in border areas, which can reduce accuracy and limit usable workspace due to spatial constraints in surgical environments.

Innovation Solution

A computer-implemented method for determining the optimal configuration of a medical robotic arm by acquiring treatment information, patient position data, and constraint information, and calculating the configuration to ensure the robotic arm can reach the required workspace while minimizing interference with personnel and equipment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the robotic arm operates in border areas of the work space or carries heavy loads, then the robotic arm can reach more positions, but the positioning accuracy deteriorates

Engineering Contradiction:
Improveworkspace reachabilityVSAvoidpositioning accuracy
Core Design Contradiction:
Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system performs preliminary calculation of the optimal robotic arm configuration before the surgical procedure begins. By pre-determining the base position and arm pose based on treatment information and patient position data, the system ensures that the robotic arm operates from optimal positions that maintain high positioning accuracy throughout the procedure, rather than attempting to reach into suboptimal border areas during surgery.

Inventive Principle:
Principle #10Preliminary action

2Adaptability or versatility

If the robotic arm is positioned to maximize workspace coverage, then more positions can be reached, but the freedom of persons involved in the surgical procedure is reduced

Engineering Contradiction:
Improveworkspace coverageVSAvoidfreedom of persons
Core Design Contradiction:
Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system optimizes the robotic arm configuration specifically for the local surgical site requirements rather than maximizing overall workspace coverage. By calculating the optimal base position and arm pose tailored to the specific treatment area and patient anatomy, the system provides sufficient workspace coverage for the surgical procedure while minimizing interference with the freedom of movement of surgical personnel.

Inventive Principle:
Principle #3Local quality

3Strength

If the robotic arm configuration is optimized for heavy load carrying, then the load capacity is improved, but the usable workspace becomes smaller

Engineering Contradiction:
Improveload capacityVSAvoidusable workspace
Core Design Contradiction:
StrengthVSAdaptability or versatility

Solution Approach 1:

The system dynamically determines the optimal robotic arm configuration based on the actual surgical requirements and patient position data. Rather than fixing the configuration for heavy load carrying, the system calculates the optimal base position and arm pose that balances load capacity requirements with the needed workspace coverage for the specific surgical procedure, allowing the configuration to be adapted to the actual operational needs.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentUS12201373B2Determining a configuration of a medical robotic arm
Publication Date: 2025.01.21 BRAINLAB AG
  • US12201373B2 patent drawing
  • US12201373B2 patent drawing
  • US12201373B2 patent drawing

AI summary

A computer implemented method for determining a configuration of a medical robotic arm, wherein the configuration comprises a pose of the robotic arm and a position of a base of the robotic arm, comprising the steps of: acquiring treatment information data representing information about the treatment to be performed by use of the robotic arm; acquiring patient position data representing the position of a patient to be treated; and calculating the configuration from the treatment information data and the patient position data.