Robotic Arm Setup Using Pose Feedback and Boundary Constraints
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Solution Overview
Problem
Robotic medical systems face challenges in setting up procedures smoothly due to factors like workspace boundaries, arm collisions, kinematic singularities, and internal instrument conflicts, leading to potential interruptions during surgery.
Innovation Solution
A robotic medical system that optimizes the pose of adjustable arm supports and robotic arms based on procedure selection and user-defined boundary conditions, using a kinematic chain with processors to adjust and compare actual and recommended poses, providing visual feedback for user adjustments to ensure safety and minimize disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic arms are manually positioned during setup, then the system can be configured for different procedures, but workspace boundaries and arm collisions may cause interruptions during surgery
Solution Approach 1:
The system performs preliminary computational analysis during the setup phase to calculate optimal robotic arm poses and workspace boundaries. By pre-computing collision-free paths and valid configuration spaces before surgery begins, the system eliminates the need for manual trial-and-error positioning, thereby ensuring procedural continuity while managing setup complexity through automated algorithms.
Solution Approach 2:
The system implements real-time feedback mechanisms that monitor robotic arm positions against pre-calculated workspace boundaries and collision constraints. During setup and surgery, the system continuously checks arm configurations and provides feedback to adjust poses, preventing collisions and interruptions. This closed-loop control ensures reliability by maintaining arms within safe operational envelopes.
2Object-affected harmful factors
If robotic arms are positioned to avoid collisions, then operator safety is improved, but the setup time and complexity increase
Solution Approach 1:
The system pre-computes collision-free workspace boundaries and valid arm poses during the setup phase, before surgery begins. By performing these computational analyses in advance, the system eliminates the need for time-consuming manual adjustments during surgery to avoid collisions. The pre-calculated safe zones and trajectories are stored and used throughout the procedure, reducing setup time while maintaining safety.
Solution Approach 2:
The system automatically calculates and adjusts robotic arm configurations to avoid collisions without requiring continuous manual intervention. The automated setup process independently computes optimal poses and validates them against workspace boundaries, enabling the system to self-configure safely. This reduces both setup time and the risk of collisions during surgery.
3Manufacturing precision
If the system provides detailed visual feedback for pose adjustments, then setup precision is improved, but the user interface complexity increases
Solution Approach 1:
The system creates visual copies or representations of the physical robotic arm poses in a graphical user interface. Instead of directly manipulating complex physical systems, users interact with simplified 2D or 3D visual models that replicate arm positions and configurations. This copying approach maintains high pose accuracy by allowing precise visual alignment while reducing interface complexity through intuitive graphical representations rather than raw numerical controls.
Solution Approach 2:
The system implements visual feedback mechanisms that display the current robotic arm pose alongside the target recommended pose. Users can visually compare actual versus desired configurations, making precise adjustments to minimize deviations. This visual feedback loop enables high setup precision by allowing users to see and correct positioning errors, while the feedback is presented through a streamlined interface that shows only the most relevant visual differences.
4Reliability
If the system automatically optimizes arm poses, then surgical interruptions are reduced, but the automation level and system complexity increase
Solution Approach 1:
The system performs automated optimization of robotic arm poses during the setup phase, calculating optimal configurations before surgery begins. By pre-computing the best arm positions and trajectories in advance, the system reduces the need for automated adjustments during surgery, thereby maintaining procedural smoothness while limiting the extent of automation required during the actual procedure. The heavy computational lifting is done beforehand.
Solution Approach 2:
The system implements automated feedback control that monitors arm positions and makes real-time adjustments to maintain optimal poses during surgery. This automated feedback mechanism reduces surgical interruptions by detecting and correcting positioning deviations without manual intervention. The system continuously compares actual poses against recommended poses and automatically adjusts, providing smooth procedure execution with moderate automation levels focused on critical real-time corrections.
Data Source
AI summary
Robotic medical systems can be capable of establishing procedural setup. A robotic medical system can include a kinematic chain having at least a first robotic arm. The robotic medical system can be configured to execute first movement of the kinematic chain to a first pose in accordance with a first recommended pose corresponding to a first procedure to be performed on a patient. After the kinematic chain reaches the first pose, the robotic medical system can obtain first data corresponding to a boundary condition of the kinematic chain in accordance with an input from a user and/or second data corresponding to a current state of the patient. The robotic medical system can be configured to adjust at least a portion of the kinematic chain from the first pose to a second pose in accordance with the obtained first data and/or second data.