A Spatial Position-based Visual Servoing Obstacle-avoidable Shape Control Framework for An 11-DOF Hybrid Continuum Robot
Puchen Zhu, Wenkai Lai, Xin Ma, Xuchen Wang, Jianshu Zhou, Shing Shin Cheng, Kwok Wai Samuel Au
Abstract
As one of the effective closed-loop control methods, visual servoing control methods are widely applied to continuum robots. However, existing visual servoing control methods mostly focus on accurate control of the robot’s end-effector, with less consideration given to the robot’s shape. In this work, a spatial position-based visual servoing obstacle-avoidable shape control framework for an 11-degree-of-freedom (DOF) hybrid continuum robot is proposed. In the control framework, a set of markers representing the shape of the continuum robot are measured and two spatial arcs are used to fit the shape. When controlling the redundant DOFs of the robot, position-based visual servoing shape control combined with obstacle avoidance is formulated as a quadratic programming problem, yielding the optimal solution at each sample time for the joint velocity vector of the 11-DOF hybrid continuum robot. Several experiments are conducted to validate the proposed control framework, which indicates the accuracy of the shape control achieves 0.88 mm.
BibTeX
@inproceedings{iros2025_aspatialposition,
title = {A Spatial Position-based Visual Servoing Obstacle-avoidable Shape Control Framework for An 11-DOF Hybrid Continuum Robot},
author = {Puchen Zhu and Wenkai Lai and Xin Ma and Xuchen Wang and Jianshu Zhou and Shing Shin Cheng and Kwok Wai Samuel Au},
booktitle = {IROS 2025},
year = {2025}
}