Deformable Object Simulation Link to heading
The existing methods of shape estimation of continuum objects create dense point clouds from camera images, and/or use distinguishable markers on a deformable body. They have natural limitations in realtime tracking of large continuum objects/manipulators and the physical occlusion of markers can often compromise accurate shape estimation. We propose a robust method to estimate the shape of linear deformable objects in realtime using scattered and unordered key points. By utilizing a robust probability-based labeling algorithm, our approach identifies the true order of the detected key points and then reconstructs the shape using piecewise spline interpolation. The proposed method is implemented in C++ and integrated with ROS. The code is available here.