VLC-SE: Visual-Lengthwise Configuration Self-Estimator of Continuum Robots

Abstract

A novel concept for visual-lengthwise configuration self-estimator (VLC-SE) of continuum robots is presented, using multiple monocular cameras mounted to each end of segments and lengths encoder as input sensors. The proposed approach grounds the improved lengths based kinematic model with Piecewise Polynomial Curvature (PPC) hypothesis, which ensures accurate modelling and avoids the flaws - as discontinuities and singularities. Meanwhile, we discussed the observability of the improved model. We propose to enhance perception by the vision of each segment end, which comes to the concept of Flexible Multi-Camera Bundle Adjustment (FMC-BA). We validate the performance of our approach on the data collected on a snake-like continuum robot. We also share the first continuum robot datasets: CoRo, including vision and arc lengths data, to promote further research. (https://cutt.ly/CoRo_dataset).