A comparison between single-stage and two-stage 3D tracking algorithms for greenhouse robotics
arxiv(2024)
摘要
With the current demand for automation in the agro-food industry, accurately
detecting and localizing relevant objects in 3D is essential for successful
robotic operations. However, this is a challenge due the presence of
occlusions. Multi-view perception approaches allow robots to overcome
occlusions, but a tracking component is needed to associate the objects
detected by the robot over multiple viewpoints. Multi-object tracking (MOT)
algorithms can be categorized between two-stage and single-stage methods.
Two-stage methods tend to be simpler to adapt and implement to custom
applications, while single-stage methods present a more complex end-to-end
tracking method that can yield better results in occluded situations at the
cost of more training data. The potential advantages of single-stage methods
over two-stage methods depends on the complexity of the sequence of viewpoints
that a robot needs to process. In this work, we compare a 3D two-stage MOT
algorithm, 3D-SORT, against a 3D single-stage MOT algorithm, MOT-DETR, in three
different types of sequences with varying levels of complexity. The sequences
represent simpler and more complex motions that a robot arm can perform in a
tomato greenhouse. Our experiments in a tomato greenhouse show that the
single-stage algorithm consistently yields better tracking accuracy, especially
in the more challenging sequences where objects are fully occluded or
non-visible during several viewpoints.
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