scholarly journals Route-Planning Method for Plant Protection Rotor Drones in Convex Polygon Regions

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2221
Author(s):  
Shaoxing Hu ◽  
Tianliang Xu ◽  
Bingke Wang
Keyword(s):  
Coordinate System ◽  
Convex Polygon ◽  
Plant Protection ◽  
Route Planning ◽  
Grid Method ◽  
Operating Efficiency ◽  
Optimal Route ◽  
Heading Angle ◽  
Waste Rate ◽  
Local Plane

Aiming at the problem of low operating efficiency due to the poor endurance of plant protection rotor drones and the small volume of pesticide carried, this paper proposes a route-planning algorithm for convex polygon regions based on the initial heading angle. First, a series of coordinate conversion methods ranging from the Earth coordinate system to the local plane coordinate system are studied. Second, in the local plane coordinate system, a route generation method based on subregion is proposed; therefore, multiple routes can be generated with different initial heading angles. Lastly, the optimal route and the best initial heading angle can be obtained after the comparison according to the three evaluation criteria: number of turns, route distance, and pesticide waste rate. The simulation results show that, compared with the common grid method, the route generation method based on subregion reduces the route distance and pesticide waste rate by 2.27% and 13.75%, respectively. Furthermore, it also shows that, compared with the route generated by the initial heading angle of 0°, the optimal route reduces the number of turns, route distance, and pesticide waste rate by 60%, 17.65%, and 38.18%, respectively. The route was optimized in three aspects and reached the best overall result using this method, which in turn proved its feasibility.

scholarly journals Capacitated vehicle routing problem model for carriers

2018 ◽  
Vol 12 ◽  
Author(s):  
Irma-Delia Rojas-Cuevas ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Jose-Rafael Mendoza-Vazquez
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Network Flow ◽  
Route Planning ◽  
Test Problems ◽  
Optimal Route ◽  
Routing Problem ◽  
Problem Model ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.

scholarly journals Real-time urban regional route planning model for connected vehicles based on V2X communication

2020 ◽  
Vol 13 (1) ◽  
pp. 517-538 ◽  
Author(s):  
Pangwei Wang ◽  
Hui Deng ◽  
Juan Zhang ◽  
Mingfang Zhang
Keyword(s):  
Land Use ◽  
Travel Time ◽  
Real Time ◽  
Land Use Planning ◽  
Route Planning ◽  
Urban Traffic ◽  
Urban Transport ◽  
Connected Vehicles ◽  
Planning Model ◽  
Optimal Route

Advancement in the novel technology of connected vehicles has presented opportunities and challenges for smart urban transport and land use. To improve the capacity of urban transport and optimize land-use planning, a novel real-time regional route planning model based on vehicle to X communication (V2X) is presented in this paper. First, considering the traffic signal timing and phase information collected by V2X, road section resistance values are calculated dynamically based on real-time vehicular driving data. Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. Finally, we design the test scenario with different traffic saturation levels and collect 150 sets of data to analyze the feasibility of the proposed method. The numerical results have shown that the average travel times calculated by the proposed optimal route are 8.97 seconds, 12.54 seconds, and 21.85 seconds, which are much shorter than the results of traditional navigation routes. This proposed model can be further applied to the whole urban traffic network and contribute to a greater transport and land-use efficiency in the future.

Optimal route planning for day tours in Marinduque, Philippines

2021 ◽  
Author(s):  
Destiny S. Lutero ◽  
Gilbert Elvis A. Cerilo ◽  
Allyssa M. Eustaquio ◽  
Christian Alvin H. Buhat ◽  
Aldrin O. Nazareno ◽  
...  
Keyword(s):  
Route Planning ◽  
Optimal Route

scholarly journals Research on Vision-Based Navigation for Plant Protection UAV under the Near Color Background

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 533 ◽  
Author(s):  
Zhang ◽  
Wang ◽  
Chen ◽  
Jiang ◽  
Lin
Keyword(s):  
Flight Control ◽  
Plant Protection ◽  
Route Planning ◽  
Visual Navigation ◽  
Recognition Method ◽  
Landmark Identification ◽  
Color Differences ◽  
Color Background ◽  
Dark Green ◽  
Landmark Location

GPS (Global Positioning System) navigation in agriculture is facing many challenges, such as weak signals in orchards and the high cost for small plots of farmland. With the reduction of camera cost and the emergence of excellent visual algorithms, visual navigation can solve the above problems. Visual navigation is a navigation technology that uses cameras to sense environmental information as the basis of an aircraft flight. It is mainly divided into five parts: Image acquisition, landmark recognition, route planning, flight control, and obstacle avoidance. Here, landmarks are plant canopy, buildings, mountains, and rivers, with unique geographical characteristics in a place. During visual navigation, landmark location and route tracking are key links. When there are significant color-differences (for example, the differences among red, green, and blue) between a landmark and the background, the landmark can be recognized based on classical visual algorithms. However, in the case of non-significant color-differences (for example, the differences between dark green and vivid green) between a landmark and the background, there are no robust and high-precision methods for landmark identification. In view of the above problem, visual navigation in a maize field is studied. First, the block recognition method based on fine-tuned Inception-V3 is developed; then, the maize canopy landmark is recognized based on the above method; finally, local navigation lines are extracted from the landmarks based on the maize canopy grayscale gradient law. The results show that the accuracy is 0.9501. When the block number is 256, the block recognition method achieves the best segmentation. The average segmentation quality is 0.87, and time is 0.251 s. This study suggests that stable visual semantic navigation can be achieved under the near color background. It will be an important reference for the navigation of plant protection UAV (Unmanned Aerial Vehicle).

scholarly journals Semantic-Aware Top-k Multirequest Optimal Route

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Shuang Wang ◽  
Yingchun Xu ◽  
Yinzhe Wang ◽  
Hezhi Liu ◽  
Qiaoqiao Zhang ◽  
...  
Keyword(s):  
Semantic Similarity ◽  
Route Planning ◽  
Location Based Services ◽  
Optimal Route ◽  
Wide Range ◽  
Potential Applications ◽  
Planning Algorithm ◽  
Keyword Searching ◽  
Path Queries ◽  
Indexing Technique

In recent years, research on location-based services has received a lot of interest, in both industry and academic aspects, due to a wide range of potential applications. Among them, one of the active topic areas is the route planning on a point-of-interest (POI) network. We study the top-k optimal routes querying on large, general graphs where the edge weights may not satisfy the triangle inequality. The query strives to find the top-k optimal routes from a given source, which must visit a number of vertices with all the services that the user needs. Existing POI query methods mainly focus on the textual similarities and ignore the semantic understanding of keywords in spatial objects and queries. To address this problem, this paper studies the semantic similarity of POI keyword searching in the route. Another problem is that most of the previous studies consider that a POI belongs to a category, and they do not consider that a POI may provide various kinds of services even in the same category. So, we propose a novel top-k optimal route planning algorithm based on semantic perception (KOR-SP). In KOR-SP, we define a dominance relationship between two partially explored routes which leads to a smaller searching space and consider the semantic similarity of keywords and the number of single POI’s services. We use an efficient label indexing technique for the shortest path queries to further improve efficiency. Finally, we perform an extensive experimental evaluation on multiple real-world graphs to demonstrate that the proposed methods deliver excellent performance.

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