  In this work, we estimate the depth in which domestic waste are located in
space from a mobile robot in outdoor scenarios. As we are doing this calculus
on a broad range of space (0.3 - 6.0 m), we use RGB-D camera and LiDAR fusion.
With this aim and range, we compare several methods such as average, nearest,
median and center point, applied to those which are inside a reduced or
non-reduced Bounding Box (BB). These BB are obtained from segmentation and
detection methods which are representative of these techniques like Yolact,
SOLO, You Only Look Once (YOLO)v5, YOLOv6 and YOLOv7. Results shown that,
applying a detection method with the average technique and a reduction of BB of
40%, returns the same output as segmenting the object and applying the average
method. Indeed, the detection method is faster and lighter in comparison with
the segmentation one. The committed median error in the conducted experiments
was 0.0298 ${\pm}$ 0.0544 m.
