Robotic weed monitoring

Acta Agriculturae Scandinavica Section B: Soil and Plant Science

Volumn 61, Issue 3, 2011, Pages 202-208

  Bochtis, D D ^a   Sorensen C G ^a   Jorgensen R N ^b   Norremark M ^a   Hameed, I A ^a   Swain, K C ^a  

^a AARHUS UNIVERSITY   (Denmark)

^b UNIVERSITY OF SOUTHERN DENMARK   (Denmark)

Author keywords

Autonomous vehicles; Farm management; Mission planning; Route planning; Sampling

Indexed keywords

EID: 78649711350     PISSN: 09064710     EISSN: 16511913     Source Type: Journal    
DOI: 10.1080/09064711003796428     Document Type: Article

References (27)

1. Berge, T. W., Renécederkvist, H., Aastveit, A. H., & Fykse H. (2008). Simulating the effects of mapping and spraying resolution and threshold level on accuracy of patch spraying decisions and herbicide use based on mapped weed data. Acta Agriculturae Scandinavica, Section B - Plant Soil Science, 58, 216-229.
2. Berge, T. W., Fykse, H., & Aastveit, A. H. (2006). Patch spraying of weeds in spring cereals: Simulated influences of threshold level and spraying resolution on spraying errors and potential herbicide reduction. Acta Agriculturae Scandinavica, Section B - Plant Soil Science, 57, 212-221.
3. Blackmore, B. S., Griepentrog, H. W., Fountas, S., & Gemtos, T. A. (2007). A specification for an autonomous crop production mechanization system. Agricultural Engineering International: the CIGR Ejournal, IX, Manuscript PM 06 032.
4. Blackmore, B. S., Griepentrog, H. W., Nielsen, H., Nørremark, M., & Resting-Jeppersen, J. (2004). Development of a deterministic autonomous tractor. In Proceedings of the CIGR International Conference, Beijing.
5. Bochtis, D. D. (2008). Planning and Control of a Fleet of Agricultural Machines for Optimal Management of Field Operations. Ph.D. Thesis, A.U.Th., School of Agriculture, Agriculture Engineering Laboratory.
6. Bochtis, D. D. & Vougioukas, S. (2008). Minimising the nonworking distance travelled by machines operating in a headland field pattern. Biosystems Engineering, 101, 1-12.
7. Bochtis, D. D., Vougioukas, S. G., & Griepentrog, H. W. (2009). A mission planner for an autonomous tractor. Transaction of ASABE, 52 (5), 1429-1440.
8. Bochtis, D. D. & Sørensen, C. G. (2009). The vehicle routing problem in field logistics: part I. Biosystems Engineering, 104 (4), 447-457.
9. Choset, H. (2001). Coverage for robotics - A survey of recent results. Annals of Mathematics and Artificial Intelligence, 31, 113-126.
10. Christensen, S., Søgaard, H. T., Kudsk, P., Nørremark, M., Lund, I., Nadimi, E. S., & Jørgensen, R. (2009). Site-specific weed control technologies. Weed Research, 49, 233-241.
11. Gerhards, R. & Christensen, S. (2003). Real-time weed detection, decision making and patch spraying in maize (Zea mays L.), sugarbeet (Beta vulgaris L.), winter wheat (Triticum aestivum L.) and winter barley (Hordeum vulgare L.). Weed Research, 43, 1-8.
12. Gerhards, R. & Oebel, H. (2006). Practical experiences with a system for site-specific weed control in arable crops using real-time image analysis and GPS-controlled patch spraying. Weed Research, 46, 185-193.
13. Heisel, T., Andreasen, C., & Ersbøl, A. K. 1996. Annual weed distribution can be mapped with kriging. Weed Research, 36, 325-337.
14. Lee, D. T. & Wong, C. K. (1980). Voronoi Diagram in L1 (L-) metrics with 2-dimensional storage applications. SIAM Journal of Computing, 9, 200-211.
15. Moshou, D., Vrindts, E., De Ketelaere, B., De Baerdemaeker, J., & Ramon, H. (2001). A neural network based plant classifier. Computers and Electronics in Agriculture, 31 (1), 5-16.
16. Moshou, D., Ramon, H., & De Baerdemaeker, J. (2002). A weed species spectral detector based on neural networks. Precision Agriculture, 3 (3), 209-223.
17. Nørremark, M., Griepentrog, H. W., Nielsen, J., & Soegaard, H. T. (2008). The development and assessment of the accuracy of an autonomous GPS-based system for intrarow mechanical weed control in row crops. Biosystems Engineering, 101, 396-410.
18. Pedersen, S. M., Fountas, S., Blackmore, B. S., Gylling, M., & Pedersen, J. L. (2004). Adoption and perspectives of precision farming in Denmark. Acta Agriculturae Scandinavica, Section B - Soil and Plant Science, 54 (1), 12-18.
19. Søgaard, H. T. & Heisel, T. (2002). Machine vision identification of weed species based on active shape models. Proceedings of the EWRS (European Weed Research Society) 12th International Symposium. Wageningen, the Netherlands.
20. Sørensen, C. G. (1999). A Bayesian Network Based Decision Support System for the Management of Field Operations, Case: Harvesting Operations. Ph.D. Thesis, Technical University of Denmark.
21. Sørensen, G. C. & Jørgensen, M. H. (2005). Intra-row weed control in organic crops - technical perspectives, capability, and operational costs. ASAE Annual Meeting, Paper number 054146.
22. Sørensen, C. G., Nørremark, M., Jørgensen, R. N., Jensen, K., Jensen, L. A., & Maagaard, J. (2007). Hortibot: Feasibility study of a plant nursing robot performing weeding operations - part IV. ASAE Annual Meeting, Minneapolis, MN. Paper number 077019.
23. Sørensen, C. G. & Bochtis, D. D. (2010). Conceptual model of fleet management in agriculture. Biosystems Engineering, 105 (1), 41-50.
24. Timmermann, C., Gerhards, R., Krohmann, P., et al. (2001). The economical and ecological impact of the site-specific weed control. In S.Blackmore&G.Sand Grenier (eds.) Third European Conference on Precision Agriculture, pp. 563-568. Montpellier.
25. Vrindts, E. & De Baerdemaeker, J. (2000). Using spectral information for weed detection in field circumstances. In Ag Eng 2000 Warwick, Eur Ag Eng Paper No 00-PA-010.
26. Walter, A. M., Heisel, T., & Christensen, S. (2001). Precision application of herbicides using injection sprayer systems. In S. Blackmore & G. Sand Grenier (eds.) Third European Conference on Precision Agriculture, pp. 611-616. Montpellier.
27. Weis, M., Ritter, C., Gutjahr, C., et al. (2008). Precision farming for weed management: techniques. Gesunde Pflanzen, 60, 171-181.