Contact Stability and Contact Safety of a Magnetic Resonance Imaging-Guided Robotic Catheter Under Heart Surface Motion

Contact force quality is one of the most critical factors for safe and effective lesion formation during catheter based atrial fibrillation ablation procedures. In this paper, the contact stability and contact safety of a novel magnetic resonance imaging (MRI)-actuated robotic cardiac ablation catheter subject to surface motion disturbances are studied. First, a quasi-static contact force optimization algorithm, which calculates the actuation needed to achieve a desired contact force at an instantaneous tissue surface configuration is introduced. This algorithm is then generalized using a least-squares formulation to optimize the contact stability and safety over a prediction horizon for a given estimated heart motion trajectory. Four contact force control schemes are proposed based on these algorithms. The first proposed force control scheme employs instantaneous heart position feedback. The second control scheme applies a constant actuation level using a quasi-periodic heart motion prediction. The third and the last contact force control schemes employ a generalized adaptive filter-based heart motion prediction, where the former uses the predicted instantaneous position feedback, and the latter is a receding horizon controller. The performance of the proposed control schemes is compared and evaluated in a simulation environment.

Scanning control based on real-time contact force feedback for ultrasonic thickness measurement

An effective contact force control strategy is of great significance for accurate and stable ultrasonic thickness on-machine measurement. However, it is difficult to adjust the contact force dynamically due to the uncertainty of the geometric characteristics of the measured workpiece. In this paper, a contact force control method based on the combination of adaptive impedance controller and sliding mode variable structure position controller is proposed. First, the control process with the force tracking impedance control and a normal contact force calculation model is established. Then, a force-position conversion model and a sliding mode variable structure controller are proposed. Further, a simulation with a typical S-shaped measured surface is given to show that the algorithm for controlling contact force can achieve good real-time tracking performance and has stronger robustness than traditional methods. Finally, an arc-shaped aluminum alloy thin-wall part thickness is sampled along the scan trajectory to verify the effectiveness of the algorithm. The experimental results show that the proposed algorithm for controlling contact force can quickly adjust the measuring device to the target position and maintain the stability of the normal contact force to ensure the accuracy of ultrasonic thickness on-machine measurement.

Neural Network Based Contact Force Control Algorithm for Walking Robots

Walking algorithms using push-off improve moving efficiency and disturbance rejection performance. However, the algorithm based on classical contact force control requires an exact model or a Force/Torque sensor. This paper proposes a novel contact force control algorithm based on neural networks. The proposed model is adapted to a linear quadratic regulator for position control and balance. The results demonstrate that this neural network-based model can accurately generate force and effectively reduce errors without requiring a sensor. The effectiveness of the algorithm is assessed with the realistic test model. Compared to the Jacobian-based calculation, our algorithm significantly improves the accuracy of the force control. One step simulation was used to analyze the robustness of the algorithm. In summary, this walking control algorithm generates a push-off force with precision and enables it to reject disturbance rapidly.