  We present a new reproducible benchmark for evaluating robot manipulation in
the real world, specifically focusing on pick-and-place. Our benchmark uses the
YCB objects, a commonly used dataset in the robotics community, to ensure that
our results are comparable to other studies. Additionally, the benchmark is
designed to be easily reproducible in the real world, making it accessible to
researchers and practitioners. We also provide our experimental results and
analyzes for model-based and model-free 6D robotic grasping on the benchmark,
where representative algorithms are evaluated for object perception, grasping
planning, and motion planning. We believe that our benchmark will be a valuable
tool for advancing the field of robot manipulation. By providing a standardized
evaluation framework, researchers can more easily compare different techniques
and algorithms, leading to faster progress in developing robot manipulation
methods.
