  Robotic manipulation of deformable materials is a challenging task that often
requires realtime visual feedback. This is especially true for deformable
linear objects (DLOs) or "rods", whose slender and flexible structures make
proper tracking and detection nontrivial. To address this challenge, we present
mBEST, a robust algorithm for the realtime detection of DLOs that is capable of
producing an ordered pixel sequence of each DLO's centerline along with
segmentation masks. Our algorithm obtains a binary mask of the DLOs and then
thins it to produce a skeleton pixel representation. After refining the
skeleton to ensure topological correctness, the pixels are traversed to
generate paths along each unique DLO. At the core of our algorithm, we
postulate that intersections can be robustly handled by choosing the
combination of paths that minimizes the cumulative bending energy of the
DLO(s). We show that this simple and intuitive formulation outperforms the
state-of-the-art methods for detecting DLOs with large numbers of sporadic
crossings ranging from curvatures with high variance to nearly-parallel
configurations. Furthermore, our method achieves a significant performance
improvement of approximately 50% faster runtime and better scaling over the
state of the art.
