Clinical Workspace Simulation for Robotic Arm Collision Avoidance
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Solution Overview
Problem
Current surgical robotic systems face lengthy setup times and do not account for potential collisions between robotic arms during surgeries, necessitating a system for virtual placement of robotic components to optimize initial setup.
Innovation Solution
A computer-implemented method for clinical workspace simulation that includes receiving user inputs for virtual object placement, rendering a virtual operating room, and determining optimized surgical parameter settings such as port and robotic arm placement, while also detecting potential collisions and providing setup guides based on simulated patient anatomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional manual setup of robotic surgical systems is used, then flexibility in adjusting component positions is maintained, but setup time becomes lengthy and collision risks increase
Solution Approach 1:
The system performs virtual placement and collision detection of robotic components before actual surgery setup. By simulating the entire surgical workspace in advance, the system determines optimal component positions and identifies potential collisions beforehand, eliminating the need for time-consuming manual adjustments during actual setup while reducing collision risks.
Solution Approach 2:
The system creates a virtual copy of the surgical operating room with accurate representations of robotic arms, surgical tables, and other equipment. This virtual model allows for repeated simulation and optimization without affecting physical equipment, enabling rapid iteration and optimization of component placement while maintaining simplicity in the physical setup process.
2Reliability
If virtual simulation system is implemented to optimize component placement, then setup time is reduced and collision risks are minimized, but system complexity and initial setup requirements increase
Solution Approach 1:
The system replaces complex manual mechanical adjustment processes with automated virtual simulation and computational algorithms. Instead of physically moving robotic components and manually checking for collisions, the system uses software-based collision detection algorithms and automated optimization routines to determine safe and efficient component placement, improving reliability while managing complexity through software rather than hardware.
Solution Approach 2:
The virtual simulation environment serves as an intermediary between the physical robotic system and the actual surgical setup. It acts as a mediator that processes component placement parameters, performs collision detection, and generates optimized configuration recommendations, thereby improving collision avoidance accuracy while isolating the complexity within the simulation layer rather than the physical system.
3Adaptability or versatility
If multiple robotic arms are positioned to access different anatomical targets, then surgical versatility is improved, but risk of collision between arms increases
Solution Approach 1:
The system performs comprehensive collision detection and trajectory analysis for multiple robotic arms before actual surgery. By simulating the movement paths and working spaces of all robotic arms in advance, the system identifies potential collision zones and adjusts arm positions or surgical approaches beforehand, enabling multiple arms to operate simultaneously with reduced collision risk while maintaining surgical versatility.
Solution Approach 2:
The system analyzes and optimizes the workspace of each individual robotic arm based on its specific anatomical target and movement characteristics. By tailoring the position, orientation, and motion constraints of each arm to its local surgical requirements, the system maximizes surgical access capability for each arm while minimizing interference and collision risk with other arms in the shared surgical space.
Data Source
AI summary
A computer-implemented method for clinical workplace simulation includes capturing a surgical parameter from one or more robotic surgical operations, based on a sensor; and determining an optimized surgical parameter based on the captured surgical parameter. The surgical parameter includes a patient habitus, a port location in a first patient, and/or a robotic arm placement relative to the first patient. The optimized surgical parameter includes an optimized port placement location in a second patient, and/or an optimized robotic arm placement location relative to the second patient.