ETH Image Based Visual Servoing to Guide Flexible Robots

Video Demo


Eye-To-Hand Image Based Visual Servoing to Guide Flexible Robots

Project goals

Flexible robots including active cannula or cable driven continuum robots are typically suitable for such minimally invasive surgeries because they are able to present various flexible shapes with great dexterity, which strengthens the ability of collision avoidance and enlarges the reachability of operation tools. Using model based control method will lead to artificial singularities and even inverted mapping in many situations because the models are usually developed in free space and cannot perform effectively in constrained environments. Therefore, the goal of this project is control the motion of a tentacle-like curvilinear concentric tube robot by model-less visual servoing.

Approaches

A two-dimensional planar manipulator is constructed by enabling only the three translation inputs of a six DOF concentric tube robot. As shown in Fig. 1, the concentric tube manipulator is controlled using a PID controller and the images captured by an uncalibrated camera are used as visual feedback.

Fig1setup

Fig. 1. The experimental setup includes a concentric tube robot, a camera, a laptop, a marker and a target.

The visual tracking of the concentric tube robot is based on shape detection. The circular marker is attached to the tip of the concentric tube robot and a square target is given for the tip to trace. During the experiments, the coordinates of the marker centroid and target centroid are calculated while the next target position is calculated at the same time as shown in Fig. 2.

Fig2workingmechanism

Fig. 2. Working mechanism of the system. Top: translations of the three tubes. Bottom: marker, final target and the next target position on the image plane.

Fig3overview

Fig. 3. Overview of the control algorithm. The Jacobian matrix is estimated based on the measurements of each incremental movement detected from the camera.

The framework of the controlling the robot is shown in Fig. 3. The initial Jacobian matrix is acquired by running each individual motor separately and measuring the change of tip position of the robot in the image space. Then the optimal control is achieved by solving a typical redundant inverse kinematics. And finally the Jacobian matrix is continuously estimated based on the measured displacements.

Results

To evaluate the proposed model-less algorithm, a simulation was carried out on MATLAB first. The desired and actual trajectory was shown in Fig. 4, from which it could be seen that the robot succeeded in following the reference trajectory and reaching the target position.

Fig4simulationcrt

Fig. 4. Simulation of using the proposed algorithm to control a concentric tube robot.

The proposed algorithm was also implemented on a physical concentric tube robot in free space. It was found the robot was able to reach goal with zero steady state error in all trials as shown in Fig. 5.

Fig5experiments

Fig. 5. The concentric tube robot is able to reach a desired goal using the proposed method. Top: the motion of the robot. Bottom: the reference and actual trajectories of two experiments.

People involved

Staff: Keyu WU, Liao WU
PI: Hongliang REN

Publications

1. Keyu Wu, Liao Wu and Hongliang Ren, “An Image Based Targeting Method to Guide a Tentacle-like Curvilinear Concentric Tube Robot”, ROBIO 2014, IEEE International Conference on Robotics and Biomimetics, 2014.

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