Implicit active constraints for concentric tube robots based on analysis of the safe and dexterous workspace
Konrad Leibrandt, Christos Bergeles, Guang-Zhong Yang
Abstract
The use of concentric tube robots has recognized advantages for accessing target lesions while conforming to certain anatomical constraints. However, their complex kinematics makes their safe telemanipulation in convoluted anatomy a challenging task. Collaborative control schemes, which guide the operator through haptic and visual feedback, can simplify this task and reduce the cognitive burden of the operator. Guaranteeing stable, collision-free robot configurations during manipulation, however, is computationally demanding and, until now, either required long periods of pre-computation time or distributed computing clusters. Furthermore, the operator is often presented with guidance paths which have to be followed approximately. This paper presents a heterogeneous (CPU/GPU) computing approach to enable rapid workspace analysis on a single computer. The method is used in a new navigation scheme that guides the robot operator towards locations of high dexterity or manipulability of the robot. Under this guidance scheme, the user can make informed decisions and maintain full control of the path planning and manipulation processes, with intuitive visual feedback on when the robot's limitations are being reached.
BibTeX
@inproceedings{iros2017_implicitactiveco,
title = {Implicit active constraints for concentric tube robots based on analysis of the safe and dexterous workspace},
author = {Konrad Leibrandt and Christos Bergeles and Guang-Zhong Yang},
booktitle = {IROS 2017},
year = {2017}
}