Robotic Wrist Friction Estimation for End Effector Tracking Error
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Solution Overview
Problem
Surgical robotic systems face challenges in accurately estimating joint friction and tracking error, which affects the precision and control of end effectors during robotic surgeries, as existing methods do not effectively quantify these factors to reduce errors.
Innovation Solution
A method is developed to estimate joint friction in robotic wrists using cable force measurements, which are then used to calculate tracking errors, allowing designers to optimize transmission stiffness and reduce friction torques through lubrication or material selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If cable stiffness is increased to reduce tracking error, then transmission stiffness is improved, but device complexity and friction losses increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting transmission stiffness through cable tension control. Instead of using a fixed stiff transmission, the system varies cable tension to achieve optimal tracking performance while minimizing friction. This allows the system to adapt stiffness parameters in real-time, resolving the contradiction between maintaining high precision and avoiding excessive device complexity.
Solution Approach 2:
The system implements dynamics by making the transmission stiffness variable rather than fixed. Cable tension is dynamically adjusted based on operational requirements, allowing the transmission system to be stiff when precision is critical and more compliant when friction reduction is needed. This dynamic adaptation resolves the contradiction by allowing both high precision and reduced complexity at different times.
2Force
If friction torques are reduced through lubrication or material selection, then joint friction is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent substitutes mechanical friction reduction methods (lubrication, special materials) with a control-based approach. Instead of modifying the mechanical transmission to reduce friction, the system uses cable tension control and friction compensation algorithms to achieve the same effect. This replaces complex mechanical solutions with simpler control mechanisms, reducing manufacturing cost while maintaining low friction performance.
Solution Approach 2:
The system implements self-service by automatically compensating for friction effects through control algorithms. Rather than requiring expensive friction-reducing materials or lubrication systems, the robotic system uses sensor feedback and control processing to detect and compensate for friction torques in real-time. This allows the system to maintain low effective friction without adding manufacturing complexity.
3Measurement precision
If cable force measurements are used to estimate joint friction, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent uses cable force measurements as an intermediary to indirectly estimate joint friction. Instead of installing friction sensors directly at the joints, the system measures cable forces and uses these measurements as intermediaries to calculate friction torques through mathematical models. This approach achieves precise friction estimation while avoiding the complexity of direct friction sensing.
Solution Approach 2:
The system replaces mechanical friction measurement devices with a computational approach. Instead of using complex sensors to directly measure friction at joints, the patent substitutes this with cable force sensors and mathematical estimation algorithms. This substitution achieves equivalent measurement precision while significantly reducing device complexity, as cable force sensors are simpler and more readily available than joint friction sensors.
Data Source
AI summary
A computerized method for estimating joint friction in a joint of a robotic wrist of an end effector. Sensor measurements of force or torque in a transmission that mechanically couples a robotic wrist to an actuator, are produced. Joint friction in a joint of the robotic wrist that is driven by the actuator is computed by applying the sensor measurements of force or torque to a closed form mathematical expression that relates transmission force or torque variables to a joint friction variable. A tracking error of the end effector is also computed, using a closed form mathematical expression that relates the joint friction variable to the tracking error. Other aspects are also described and claimed.