Continuous-Time Filter Library for Multi-Rate Robotic Control
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Solution Overview
Problem
Designing filters for surgical robotic systems with varying control rates across different components and modes is challenging due to differing signal and data filtering requirements, leading to inefficiencies and increased time in development.
Innovation Solution
A scalable filtering infrastructure is implemented using a library of continuous-time filters that are discretized for specific control rates, allowing for rapid generation of filters suitable for different components and modes within the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If filters are designed for each specific control rate separately, then filter performance for that control rate is optimized, but the complexity of filter design and the time required to design appropriate filters increases significantly
Solution Approach 1:
The patent segments the filter design process by separating the continuous-time filter definition from the discrete-time implementation. A library of continuous-time filter definitions is created once, and then these definitions are discretized for different control rates. This segmentation allows the same continuous-time definition to serve multiple discrete-time applications at different rates, reducing design complexity while maintaining performance.
Solution Approach 2:
The patent uses parameter changes by taking a continuous-time filter definition and transforming it into discrete-time representations for different sampling rates. The continuous-time filter parameters (coefficients, poles, zeros) are transformed into discrete-time equivalents using methods like bilinear transform or matched poles. This parameter transformation allows a single filter design to adapt to multiple control rates without redesigning the filter from scratch.
2Productivity
If a library of continuous-time filters is created and discretized for different control rates, then filter generation speed and versatility improve, but the computational steps required for discretization and filter generation increase
Solution Approach 1:
The patent applies preliminary action by pre-defining a library of continuous-time filter characteristics before they are needed for specific applications. These continuous-time filter definitions are created once with optimal parameters for their intended function. When a specific control rate is required, the pre-defined continuous-time filter is discretized to generate the discrete-time filter coefficients. This preliminary preparation eliminates the need to redesign filters from scratch for each application, significantly improving generation speed.
Solution Approach 2:
The patent uses copying by creating discrete-time filter coefficients as copies or transformations of the continuous-time filter definitions. Instead of redesigning filters for each control rate, the system copies the continuous-time filter structure and transforms the parameters to match the desired discrete-time sampling rate. This copying approach maintains the essential filter characteristics while adapting to different control rates efficiently.
3Adaptability or versatility
If distributed components operate at different sampling rates, then system adaptability to different modes of operation improves, but the difficulty of designing appropriate filters for each component increases
Solution Approach 1:
The patent implements universality by creating a single library of continuous-time filter definitions that can serve multiple functions across different distributed components operating at different sampling rates. Each continuous-time filter definition in the library can be discretized to match the specific control rate of any component. This universal approach allows the same filter library to support robot components, user console components, and communication components all operating at their respective optimal rates without requiring separate filter designs for each component type.
Data Source
AI summary
For a scalable filtering infrastructure, a library of filters each usable at different control rates is provided by defining filters in a continuous time mode despite eventual use for digital filtering. For implementation, a filter is selected and discretized for the desired control rate. The discretized filter is then deployed as a discrete time realization for convolution. In a distributed system with multiple control rates, the library may be used to more rapidly and conveniently generate the desired filters.