ArticleCyborg and bionic systems (Washington, D.C.)2025
Model-Based Control of a Continuum Manipulator with Online Jacobian Error Compensation Using Kalman Filtering.
Article in Cyborg and bionic systems (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A Prediction-Enhanced Polynomial Kalman Filter Using Higher-Order Predictive Representations for State Estimation.Sensors (Basel, Switzerland) · 2026Article
- Design and Implementation of a Three-Segment Tendon-Driven Continuum Robot with Variable Stiffness for Manipulation in Confined Spaces.Biomimetics (Basel, Switzerland) · 2026Article
- Enhancing Shape Sensing of Slender Medical Continuum Robot Using Carbon Nanotube Piezoresistive Fiber Bandage.Cyborg and bionic systems (Washington, D.C.) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Flexible continuum robots exhibit excellent adaptability to a wide range of tasks and environments. However, accurate and efficient modeling and control remain challenging due to their inherent nonlinearities. In this article, a hybrid model-based and online data-driven control method is proposed for a tendon-driven continuum robot, which requires no prior dataset collection or training. The method incorporates the Jacobian derived from the piecewise constant curvature model with online Jacobian error compensation using a Kalman filter. Consecutive Jacobian estimates are constrained to reduce fluctuations and improve stability in real-time estimation. Experimental results validate the effectiveness of the proposed hybrid approach in enhancing tracking accuracy and demonstrate its robustness against external disturbances.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.