We’re thrilled to share our work, “Inconstant curvature kinematics of parallel continuum robot without static model”, which has been accepted at the IEEE International Conference on Robotics and Automation (ICRA 2024)!

In the study of minimally invasive surgical robots, a mini parallel continuum robot (PCR) has shown motion advantage after passing through a long and winding working channel. However, due to the interaction force between the elastic wires of the parallel robots during motion generation processes, the constant curvature assumption has shown modeling errors. This causes the current geometric kinematic model to become unreliable. This paper aims to solve this issue. The simulation in ANSYS is carried out, and the shape of one of the driving wires, when bending, is fitted by a two-segment polynomial curve. Then, the position of the distal wrist tip can be calculated based on the curve shape. To verify the accuracy of the proposed model, bending simulation and experiment are carried out. The accuracy of the proposed model is compared with that of the kinematic model based on constant curvature assumption. The result shows that the proposed model can get more accurate results, especially when the driving wire displacement increases.

Main contributions:

1. A two-segment polynomial curve was used to model the deformation of the parallel wrist joint. Compared with the kinematic model based on constant curvature assumption, the proposed curve has shown higher accuracy. 

2. The fitting results of the chosen NiTi wire with the proposed curve were verified by finite element simulation (Fig. 3).

3. The modeling accuracy was verified when the deflection angle was 0ยฐ, 30ยฐ and 45ยฐ respectively. The experimental results show that the accuracy of this method is improved significantly than that of the constant curvature model. Especially, when the bending angle is increased, its accuracy does not decrease significantly.

Stay tuned to more of our research on parallel continuum robot!!!

Co-authors: Tao Zhang, Huxin Gao and Prof Hongliang Ren.

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