Tendon-Driven Continuum Manipulator Navigation via Distal Sensor Estimation
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Solution Overview
Problem
Autonomous control of tendon-driven continuum manipulators in minimally invasive surgeries, such as bronchoscopies, is challenging due to the decoupled passive and articulating regions and the lack of accurate sensor feedback, leading to variability in diagnostic yield and navigation difficulties in constrained anatomical environments.
Innovation Solution
The method estimates the orientation of the articulating region's base using existing distal tip sensors, employing kinematic models and nonlinear filters to enable autonomous closed-loop control of flexible tendon-driven continuum manipulators without additional sensors, allowing for task-space control and navigation through constrained anatomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional task-space control techniques are used with accurate models, then control precision is improved, but the system cannot adapt to unsensed anatomical constraints that change device conformation
Solution Approach 1:
The system uses feedback from the distal position sensor to continuously update the estimated orientation of the base of the articulating region. This feedback loop allows the control system to adapt to changing anatomical constraints by comparing the desired trajectory with the actual device position and adjusting control commands accordingly, resolving the contradiction between model accuracy and environmental adaptability.
Solution Approach 2:
The system estimates the base orientation using only the existing distal tip position sensor, without requiring additional sensors or external assistance. The kinematic model and nonlinear filter work together to self-determine the device state from available measurements, enabling autonomous adaptation to anatomical constraints while maintaining control precision.
2Adaptability or versatility
If additional sensors are introduced to sense manipulator conformation, then adaptability is improved, but device complexity and cost increase
Solution Approach 1:
The system uses the existing distal tip position sensor to estimate the base orientation through kinematic modeling, eliminating the need for additional sensors along the manipulator body. This self-service approach extracts maximum information from the available sensor, achieving full state estimation without increasing device complexity or cost.
Solution Approach 2:
The kinematic model acts as an intermediary that transforms the distal tip position measurements into base orientation estimates. This mathematical mediator enables the system to infer unmeasured states from measured states, providing sensing capability without physical sensors at every location.
3Reliability
If a second position sensor is added at the base of the manipulator, then closed-loop control is improved, but device complexity increases
Solution Approach 1:
The nonlinear filter and kinematic model serve as intermediaries that compute the base orientation from the distal tip position sensor data. This mathematical intermediary provides the necessary state information for closed-loop control without requiring a physical second sensor, maintaining reliability while minimizing device complexity.
Solution Approach 2:
The system replaces the mechanical/physical second sensor with a computational model and filter algorithm. This substitution uses software-based estimation to provide the orientation information that a second physical sensor would provide, reducing hardware complexity while maintaining control reliability.
4Ease of operation
If the manipulator has a decoupled passive region for compliance, then ease of operation is improved, but measurement precision of device state deteriorates
Solution Approach 1:
The system uses feedback from the distal position sensor combined with a kinematic model to continuously estimate the base orientation, compensating for the lack of direct measurements in the passive region. This feedback mechanism maintains measurement precision despite the compliance-induced conformation changes in the decoupled passive region.
Solution Approach 2:
The kinematic model acts as an intermediary that bridges the gap between the distal sensor measurements and the base orientation state. This mathematical mediator enables accurate state estimation even when the passive region undergoes unsensed conformations, maintaining measurement precision while preserving operational compliance.
Data Source
AI summary
Autonomous closed loop control of a flexible tendon-driven continuum manipulator having a sensor at a distal tip is performed by measuring spatial attributes of a sensor at the distal tip and estimating an orientation of a base of an articulating region of the flexible tendon-driven continuum manipulator from a kinematic model and the spatial attributes of the sensor. The manipulator control in a task space uses the estimated orientation, a desired trajectory in the task space, and the position of the sensor at the distal tip. The sensor at the distal tip may be a magnetic sensor, impedance sensor, or optical sensor.