Name
Abstract | ||
|---|---|---|
Sub-optimal pesticide application not only results in wastage and low yield but is also associated with harmful effects to the environment. To ensure optimal application of pesticide, a dynamic approach for pesticide management is required. Existing works do not consider the dynamic demand of pesticide and are based on static models. To solve these issues, this paper proposes a technique for the vehicle routing problem (VRP) in pesticide application. The proposed technique is based on dynamic predictive control, i.e., at each time step, the current demand is fed into a model predictive control algorithm which optimizes the vehicular assignment as well as routing to a specific area in an agricultural field. The proposed technique considers charging as well as capacity constraints for the autonomous vehicles. Simulations in MATLAB/Simulink show that the proposed technique not only resulted in at least 20% faster field coverage time but also consumed at least 22% less charge as compared to existing techniques for agricultural VRP. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.compag.2021.106217 | COMPUTERS AND ELECTRONICS IN AGRICULTURE |
Keywords | DocType | Volume |
Precision Agriculture, Pesticide, Autonomous Mobility | Journal | 186 |
ISSN | Citations | PageRank |
0168-1699 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Umar Zangina | 1 | 0 | 0.68 |
| Salinda Buyamin | 2 | 0 | 0.68 |
| Muhammad Aman | 3 | 62 | 13.40 |
| Mohamad Shukri Zainal Abidin | 4 | 0 | 0.68 |
| Mohd Saiful Azimi Mahmud | 5 | 0 | 0.68 |