Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach

With the development of aviation agricultural technology,the number of farmers adopting the use of drones in daily agricultural activities is growing rapidly in recent decades.Among these,a large portion constitutes agricultural drones being used in pest control and crop protection practices,e.g.agriculture spraying of pesticides.Spraying pesticides with drones have proven to be faster than other traditional methods.On the downside,flight time and range of Unmanned Aerial Vehicles(UAV)are often limited.Thus,a proper arrangement of flight height and velocity will greatly improve spraying efficiency.A new strategy to optimize the flight parameters,i.e.flight height and flight velocity,for fixed-wing UAV with a 3D simulation-based approach together with an automatic optimization algorithm was proposed in this study.To find the optimal parameters for a UAV to fly and spray under certain environmental conditions,a three-dimensional model of the target crop was established first,followed by a detailed simulation of droplet spraying.As a demonstration case,a grass model was developed and used as the target plant,and a physics-based method was used to simulate realistically the movement of the droplets in the air as well as the interaction between the droplets and the plant to obtain the droplet deposition rate under the specified operating parameters.Furthermore,the standard Particle Swarm Optimization(PSO)algorithm was used to optimize the UAV operating parameters to obtain the best operating parameters.The results indicate that using the standard PSO algorithm to optimize the operating parameters of the drone could significantly improve the deposition rate and find the best operating parameters.

New collision detection method for simulating virtual plant populations

Detecting and resolving the collision of organs between different plants or the collision of different organs of a single plant are key issues in the realistic construction of a virtual plant population.A suitable collision detection scheme is necessary to prevent a reduction in realism caused by organ penetration.A mixed bounding volume tree construction scheme based on the growth characteristics of tomato plants is proposed in this paper,and the construction mode of the bounding at all levels is simplified by using a digital tomato model.Using a parallel GPU approach,we designed a tomato plant population collision detection program with CUDA acceleration.The proposed method reduces the total collision detection time by 92%-96%.

Physics-based algorithm to simulate tree dynamics under wind load

Rapid development in the different computer science fields during the recent decades has facilitated the creation of new applications in the area of dynamic simulation of plant development.Among these new applications,simulation of trees swaying in the wind is of great importance,as those computer graphics related areas,e.g.,computer games,tree cultivation and forest management simulations,help a lot in revealing the mechanisms of tree dynamics under wind load.However,it is a big challenge to balance the effect of visualization in real time and calculation efficiency for any simulation algorithm.A physics-based algorithm to simulate tree dynamics under wind load was proposed in this study.A mechanistic model simulating the bending of a cantilever beam was used within the algorithm to simulate deformation of stems,and the algorithm was integrated with a landscape model in which different types of trees were constructed with an L-system-based formalism.Simulation results show that realistic dynamic effects can be achieved with reasonably high computational efficiency.

Optimization method to obtain appropriate spacing parameters for crop cultivation

Considering the time-consuming and tedious work of the current methods to control plant layout,which is mostly based on expert experience or field trials,we propose an algorithm to optimize and simulate a planting layout based on a virtual plant model and an optimization algorithm.A functional-structural plant model,which combines the structure and physiological function of plants,is used to construct a planting scene.The planting and row spacing are set as the genetic factors and the chromosomes of the genetic algorithm are encoded with a binary method.The photosynthetic yield of the unit planting area is denoted as the fitness value.By using this method,the intercropping of maize and soybean plants and the sole cropping of rice plants are studied.Experimental results show that the proposed method can obtain a high yield planting plan.

Simulation and visualization of spraying droplets behavior and deposition within virtual rice canopy

Models for accurately simulating pesticide droplet deposition and transmission mechanism in rice canopies can provide an effective and economic tool to optimize methods for spraying pesticides,adjuvant formulation,and spray parameters.However,the current studies on the modeling of spray droplet deposition within rice plants are still very limited.Aiming at this problem,a method to model and visualize spray transmission and deposition within the canopy of rice plants was proposed.Firstly,a particle system was used to simulate the spraying scene of droplets.Then an improved method to determine the behavior of rebound and shatter of the droplets in the virtual scene was proposed.The deposition of spraying droplets on a leaf was calculated according to the inclination angles of the leaf,the characteristics of the leaf surface,and the physical and spatial characteristics of the droplets.The experiment shows that the method can simulate the behavior of the spraying droplets within a virtual scene of a rice plant,which may provide a reference for the study of spray deposition in the canopy of the crop.