A spraying path planning algorithm based on colour-depth fusion segmentation in peach orchards

Gao, Guandong; Xiao, Ke; Jun, Yu

doi:10.1016/j.compag.2020.105412

Cited by 32 publications

(11 citation statements)

References 24 publications

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“…They reported no significant difference existed between LWA of peach and apricot trees of the same size and shape. In the recent study, a novel color-depth fusion segmentation method (CDFS) for collecting the LWA information was proposed [ 67 ].…”

Section: Core Components and Technologies For Precision Sprayingmentioning

confidence: 99%

Opportunities and Possibilities of Developing an Advanced Precision Spraying System for Tree Fruits

Mahmud

Zahid

et al. 2021

Sensors

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Reducing risk from pesticide applications has been gaining serious attention in the last few decades due to the significant damage to human health, environment, and ecosystems. Pesticide applications are an essential part of current agriculture, enhancing cultivated crop productivity and quality and preventing losses of up to 45% of the world food supply. However, inappropriate and excessive use of pesticides is a major rising concern. Precision spraying addresses these concerns by precisely and efficiently applying pesticides to the target area and substantially reducing pesticide usage while maintaining efficacy at preventing crop losses. This review provides a systematic summary of current technologies used for precision spraying in tree fruits and highlights their potential, briefly discusses factors affecting spraying parameters, and concludes with possible solutions to reduce excessive agrochemical uses. We conclude there is a critical need for appropriate sensing techniques that can accurately detect the target. In addition, air jet velocity, travel speed, wind speed and direction, droplet size, and canopy characteristics need to be considered for successful droplet deposition by the spraying system. Assessment of terrain is important when field elevation has significant variability. Control of airflow during spraying is another important parameter that needs to be considered. Incorporation of these variables in precision spraying systems will optimize spray decisions and help reduce excessive agrochemical applications.

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Section: Core Components and Technologies For Precision Sprayingmentioning

confidence: 99%

Opportunities and Possibilities of Developing an Advanced Precision Spraying System for Tree Fruits

Mahmud

Zahid

et al. 2021

Sensors

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“…The spraying process is carried out depending on the severity of disease of the plantation, which ranges from moderate to low. On the other hand in the work of [29] proposed a method to solve the route planning problem for precise spraying in peach orchards.They used a binocular color depth sensor to acquire video images in peach orchards. Then, a color depth fusion segmentation method (CDFS) based on the leaf wall area (LWA) of the color depth images was proposed.…”

Section: Path Planningmentioning

confidence: 99%

Coverage Path Planning for Spraying Drones

Vazquez-Carmona¹,

Vasquez²,

Lozada³

et al. 2021

Preprint

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The COVID-19 pandemic is causing a devastating effect on the health of global population. There are several efforts to prevent the spread of the virus. Among those efforts, cleaning and disinfecting public areas has become an important task. This task is not restricted a to disinfection, but it is also applied to painting or precision agriculture. Current state of the art planners determine a route, but they do not consider that the plan will be executed in closed areas or they do not model the sprinkler coverage. In this paper, we propose a coverage path planning algorithm for area disinfection, our method considers the scene restrictions as well as the sprinkler coverage. We have tested the method in several simulation scenes. Our experiments show that the method is efficient and covers more areas with respect to current methods.

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“…However, the first fashion is mainly dedicated to applications on surveillance, obstacle avoidance, inspection, mapping, and reconnaissance of areas. Only four papers were dedicated to the CPP problem addressing the spraying task ( Maguteeswaran et al, 2414 , Gao et al, 2020 , Yao et al, 2016 , Muliawan et al, 2019 ). In general, for crop areas, they neither consider the model of the sprinkler nor the collisions that may occur in the surrounding area.…”

Section: Introductionmentioning

confidence: 99%