**6. Conclusions**

In this work, we designed and constructed a low-cost autonomous robot (DARob) to facilitate the capture of images in agricultural fields. There are some important features to highlight about DARob:


During the operation of the robot, some limiting points were observed:


Furthermore, we created a new dataset for segmentation of plants and weeds in bean crops. In total, 228 RGB images with a resolution of 704 × 480 pixels were annotated containing 75.10% soil area, 17.30% crop area and 7.58% weed area. The benchmark results were provided by training the dataset using four different deep learning segmentation models.

**Author Contributions:** Data curation, G.J.Q.V. and G.S.R.C.; formal analysis, T.V.S. and H.P.; funding acquisition, H.P.; methodology, G.J.Q.V., G.S.R.C., T.V.S. and H.P.; writing—original draft, G.J.Q.V.; writing—review and editing, T.V.S. and H.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available in the main text.

**Conflicts of Interest:** The authors declare no conflict of interest.
