Path Planning Algorithms Benchmarking for Grapevines Pruning and Monitoring

Magalhães, Sandro Augusto; Santos, Filipe Neves dos; Martins, Rui C.; Rocha, Luís F.; Brito, José Carlos

doi:10.1007/978-3-030-30244-3_25

Cited by 10 publications

(7 citation statements)

References 14 publications

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“…The results indicated a comparison of efficiency and repeatability of particular planners for a planning scene imitating conditions in a greenhouse or similar pick-and-place tasks. Magalhães et al [11] suggested benchmarking path planner algorithms from Open Manipulator Planning Library (OPML) for tree pruning tasks. Thus, the results demonstrated good agreement for the BiTRRT algorithm compared with other algorithms from the OMPL library, such as BKPIECE, LBKPIECE, SBL, and others.…”

Section: A Motion Planning Benchmarkingmentioning

confidence: 99%

Benchmarking of Motion Planning Algorithms with Real-time 3D Occupancy Grid Map for an Agricultural Robotic Manipulator

Vaghefi,

Ibrahim,

Zaman

2022

IJACSA

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The performance evaluation of motion planning algorithms for agricultural robotic manipulators is commonly performed via benchmarking platforms. However, creating a realistic benchmarking scene that constrains the motion planning algorithms with the characteristic of a real-work environment has always been a challenge worthy of research. In this paper, we present a lab-setup benchmarking platform to evaluate Open Motion Planning Library (OMPL) motion planners for the application of a robotic harvester of a palm-like tree using a real-time 3D occupancy grid map. First, three motion problems were defined with different levels of complexity based on a real oil palm fruit harvesting task. To achieve reliable outcomes, the benchmarking scene was modeled by converting point cloud data from a stereo-depth sensor into a 3D occupancy grid map using the Octomap algorithm. Then the benchmarking was performed, all within a real-time process. According to the results, a fair performance evaluation was achieved by modeling a realistic benchmarking scene, which can help in choosing a highperforming algorithm and efficiently conducting such harvesting tasks in real practice.

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Section: A Motion Planning Benchmarkingmentioning

confidence: 99%

Benchmarking of Motion Planning Algorithms with Real-time 3D Occupancy Grid Map for an Agricultural Robotic Manipulator

Vaghefi,

Ibrahim,

Zaman

2022

IJACSA

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“…The robotic system and manipulator are show in Figures 1 and 2, respectively. Magalhães et al (2019) benchmarked different path planning algorithms on a simulated pruning manipulator with a mobile base, based on an existent manipulator, shown in Figure 3, for pruning grapevines in steep slope vineyards. The manipulator is a 6 DoF Robotis Manipulator-H.…”

Section: Robotic System To Prune Grape Vinesmentioning

confidence: 99%

“…Additionally, it was verified that these manipulators present challenges concerning path planning. Although Magalhães et al (2019) successfully planned the path for a manipulator using different algorithms, it took much longer than a human would take to determine a path. You et al (2020) managed to obtain lower planning times, but their manipulator took a high amount of time to execute the path, making it also inefficient when compared to a human.…”

Section: Analysis and Comparisonmentioning

confidence: 99%

An overview of pruning and harvesting manipulators

Tinoco

Silva

Santos

et al. 2021

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Purpose The motivation for robotics research in the agricultural field has sparked in consequence of the increasing world population and decreasing agricultural labor availability. This paper aims to analyze the state of the art of pruning and harvesting manipulators used in agriculture. Design/methodology/approach A research was performed on papers that corresponded to specific keywords. Ten papers were selected based on a set of attributes that made them adequate for review. Findings The pruning manipulators were used in two different scenarios: grapevines and apple trees. These manipulators showed that a light-controlled environment could reduce visual errors and that prismatic joints on the manipulator are advantageous to obtain a higher reach. The harvesting manipulators were used for three types of fruits: strawberries, tomatoes and apples. These manipulators revealed that different kinematic configurations are required for different kinds of end-effectors, as some of these tools only require movement in the horizontal axis and others are required to reach the target with a broad range of orientations. Originality/value This work serves to reduce the gap in the literature regarding agricultural manipulators and will support new developments of novel solutions related to agricultural robotic grasping and manipulation.

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“…An integrated pruning robotic system may consist of cameras, manipulators, a computer, sensors, and a cabin platform containing other system parts and straddling the vine row [3,4]. Few studies have been reported on a robotic pruning system [3,[5][6][7][8][9][10], most of which did not focus on the manipulators' mechanical design-which can significantly enhance the manipulator's operational performance-and rather concentrated on machine vision, algorithm design, and path planning issues. Furthermore, a cane pruning robot has never been designed; the main focus of previous studies was on spar pruning [3,9].…”

Section: Introductionmentioning

confidence: 99%

Kinematic-Based Multi-Objective Design Optimization of a Grapevine Pruning Robotic Manipulator

Molaei

Ghatrehsamani

2022

AgriEngineering

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Annual cane pruning of grape vineyards is a time-consuming and labor-intensive job, but no mechanized or automatic way has been developed to do it yet. Robotic pruning can be a perfect alternative to human labor. This article proposes a systematic seven-stage procedure to design a kinematically optimized manipulator, named ‘Prubot’, to manage vineyards’ cane pruning. The manipulator structure was chosen, resulting in a 7R (Revolute) manipulator with a spherical shoulder and wrist. To obtain the design constraints, the manipulator task space was modeled. The robot’s second and third link lengths were determined by optimizing the global translational version of the measure of manipulability and the measure of isotropy of the manipulator arm section. Finally, simulations confirmed the appropriateness of the manipulator workspace. Furthermore, sampling-based path planning simulations were carried out to evaluate the manipulator’s kinematic performance. Results illustrated the impressive kinematic performance of the robot in terms of path planning success rate (≅100%). The simulations also suggest that among the eight single-query sampling-based path planning algorithms used in the simulations, Lazy RRT and KPIECE are the best (≤5 s & ~100%) and worst (≥5 s & ~25%) path planning algorithms for such a robot in terms of computation time and success rate, respectively. The procedure proposed in this paper offers a foundation for the kinematic and task-based design of a cane pruning manipulator. It could be promisingly used for designing similar agricultural manipulators.

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Path Planning Algorithms Benchmarking for Grapevines Pruning and Monitoring

Cited by 10 publications

References 14 publications

Benchmarking of Motion Planning Algorithms with Real-time 3D Occupancy Grid Map for an Agricultural Robotic Manipulator

Benchmarking of Motion Planning Algorithms with Real-time 3D Occupancy Grid Map for an Agricultural Robotic Manipulator

An overview of pruning and harvesting manipulators

Kinematic-Based Multi-Objective Design Optimization of a Grapevine Pruning Robotic Manipulator

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