Visual Trocar Docking for Robotic Arm Alignment
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Solution Overview
Problem
Existing robotic surgical systems face challenges in efficiently and accurately docking a robotic arm to a trocar, requiring manual alignment and latching, which can be cumbersome and prone to errors.
Innovation Solution
A robotic arm system equipped with visual sensors and processors that determine the position and orientation of a trocar through image processing, guiding the arm's actuators to align and mechanically couple with the trocar automatically or with assisted manual guidance, using a planned trajectory and resistance mechanisms to maintain alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual alignment and latching is used for docking the robotic arm to the trocar, then the operator has control over the docking process, but the process becomes cumbersome and prone to errors
Solution Approach 1:
The patent replaces the purely manual mechanical alignment process with an automated system that uses visual sensors (cameras) to detect trocar position and orientation, image processing algorithms to compute alignment, and actuators to execute precise docking movements. This substitution eliminates manual alignment efforts while maintaining high docking accuracy and reducing errors.
Solution Approach 2:
The docking system performs self-alignment by automatically detecting the trocar's position and orientation, calculating the required transformation, and executing the docking sequence without requiring operator intervention for alignment. The system serves itself by autonomously completing the docking task that previously required manual operation.
2Measurement precision
If automated docking using visual sensors and image processing is implemented, then docking precision is improved, but device complexity increases
Solution Approach 1:
The visual sensor system serves multiple functions: it detects trocar position, determines trocar orientation, tracks docking progress, and provides feedback for alignment. By making the sensor system multi-functional, the patent reduces the need for separate dedicated components for each function, thereby managing complexity while achieving high measurement precision.
Solution Approach 2:
The patent introduces an intermediary computational layer (image processing algorithms and control software) that mediates between the visual sensors and the mechanical actuators. This intermediary layer processes sensor data, calculates transformations, and generates control commands, simplifying the overall system architecture by centralizing intelligence in software rather than requiring complex hardware for each function.
3Productivity
If the robotic arm is guided along a planned trajectory using actuators, then docking efficiency is improved, but the system requires precise control mechanisms
Solution Approach 1:
The patent implements feedback control by continuously monitoring the actual position and orientation of the robotic arm during docking, comparing it with the planned trajectory, and adjusting actuator commands in real-time. This feedback mechanism enables precise control while maintaining high docking speed, as the system can correct deviations automatically without requiring overly complex control hardware.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates precise and efficient robotic arm docking to trocars, reducing manual effort and enhancing surgical precision and safety by ensuring accurate alignment and mechanical coupling.
Implementation Method 1
an imaging sensor, for example, as part of an imaging system, e.g., a camera
Data Source
AI summary
A surgical robotic system has a tool drive coupled to a distal end of a robotic arm that has a plurality of actuators. The tool drive has a docking interface to receive a trocar. The system also includes one or more sensors that are operable to visually sense a surface feature of the trocar. One or more processors determine a position and orientation of the trocar, based on the visually sensed surface feature. In response, the processor controls the actuators to orient the docking interface to the determined orientation of the trocar and to guide the robotic arm toward the determined position of the trocar. Other aspects are also described and claimed.