Surgical Robot Collision Detection Using 3D Spatial Grids
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing robotic surgical systems face challenges in identifying and mitigating potential collisions between controlled components and objects within a surgical environment, leading to risks of mechanical interference during procedures.
Innovation Solution
A surgical robotic collision detection system utilizing an imaging device and a controller to generate a grid of spatial points from captured images, detect potential collisions based on a generated grid, and transmit control signals to adjust robotic arm movements to avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robotic arms make significant positional adjustments to move within the surgical field, then the productivity and effectiveness of surgical procedures is improved, but the risk of collisions between controlled components and objects increases
Solution Approach 1:
The system performs preliminary collision detection by generating a grid of spatial points and analyzing potential collision paths before the robotic arm executes its movement. The controller identifies objects within the field of vision and calculates whether the planned trajectory intersects with any objects, allowing preventive action to be taken before the harmful collision occurs.
Solution Approach 2:
The system continuously monitors the surgical environment using an imaging device to capture images and update the spatial grid in real-time. This feedback loop allows the controller to adjust the robotic arm's trajectory dynamically based on detected objects and potential collision risks, enabling safe operation during significant positional adjustments.
2Reliability
If the robotic arm is equipped with imaging devices and collision detection capabilities, then the safety and reliability of surgical procedures is improved, but the device complexity increases
Solution Approach 1:
The imaging device serves multiple functions: it captures images for collision detection, provides visual feedback for surgical guidance, and enables spatial mapping of the surgical environment. The controller performs both collision detection algorithms and surgical control functions, reducing the need for separate dedicated systems and thereby managing complexity while maintaining enhanced safety.
Data Source
AI summary
Systems and methods for surgical robotic collision detection in accordance with aspects of the present disclosure are disclosed. In various embodiments, a system for surgical robotic collision detection includes a robotic cart having a robotic arm, an imaging device supported by the robotic cart or the robotic arm, the imaging device captures images within a field of vision of the imaging device, and a controller in operable communication with the robotic arm and the imaging device. The controller includes a processor and a memory storing instructions which, when executed by the processor, causes the controller to: receive the images from the imaging device, generate a grid including a first plurality of spatial points from the images, and detect a potential collision within the field of vision based on the generated grid.