Online Coverage Planning for an Autonomous Weed Mowing Robot With Curvature Constraints

Maini, Parikshit; Gönültaş, Burak Miraç; Isler, Volkan

doi:10.1109/lra.2022.3154006

Cited by 13 publications

(4 citation statements)

References 25 publications

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“…It can function effectively without prior knowledge of the workspace, making it versatile and adaptable to various scenarios and changing environments. In contrast, several other approaches often rely on prior knowledge of the workspace, limiting their adaptability to dynamic settings [40], [13], [58], [66], [71], [77]. Complete and non-repetitive coverage is a key focus of the proposed algorithm, ensuring that all areas are covered without unnecessary revisits to already explored regions.…”

Section: Resultsmentioning

confidence: 99%

“…The study in [39] introduces a robotic system for automated breast ultrasound scanning that ensures full and uniform coverage by employing 3-D point cloud searching and addressing tissue deformation through a contact forcestrain regression model and probe-tissue interaction adjustments, ultimately demonstrating effective maintenance of probe posture and contact force during scanning. In [40] the authors present Cowbot, an autonomous weed mowing robot designed for maintaining cow pastures, addressing the challenge of unknown weed distribution by developing online planning algorithms that optimize path length based on weed detection, validated through field and simulation experiments demonstrating significant path length reduction compared to traditional approaches. In [41] the work presents an integrated approach for coverage path planning with unmanned aerial vehicles (UAVs), optimizing both mobility and camera orientation to achieve comprehensive coverage based on visibility constraints, addressed as a constrained optimal control problem and solved using mixed integer programming optimization.…”

Section: Journal Ofmentioning

confidence: 99%

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Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Nair

2024

Journal of Robotics and Control

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In this paper, we introduce an efficient path planning algorithm designed for floor cleaning applications, utilizing the concept of Spanning Tree Coverage (STC). We operate under the assumption that the environment, i.e., the floor, is initially unknown to the robot, which also lacks knowledge regarding obstacle positions, except for the workspace boundaries. The robot executes alternating phases of exploration and coverage, leveraging the local map generated during exploration to construct a STC tree, which then guides the subsequent coverage (cleaning) phase. The extent of exploration is determined by the range of the robot's sensors. The path generation algorithms for cleaning fall within the broader category of coverage path planning (CPP) algorithms. A key advantage of this algorithm is that the robot returns to its initial position upon completing the operation, minimizing battery usage since sensors are only active during the exploration phase. We classify the proposed algorithm as an offline-online scheme. To validate the effectiveness and non-repetitive nature of the algorithm, we conducted simulations using VRep/MATLAB environments and implemented real-time experiments using Turtlebot in the ROS-Gazebo environment. The results substantiate the completeness of coverage and underscore the algorithm's significance in applications akin to floor cleaning.

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Section: Resultsmentioning

confidence: 99%

Section: Journal Ofmentioning

confidence: 99%

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Nair

2024

Journal of Robotics and Control

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“…Existing solutions mostly include specialized, task-based, agricultural robots, i.e., robots that can perform a particular task for a specific set of field conditions, but are not suitable for other tasks. Recent literature reports different robotic and mobile robotic applications in agriculture for, e.g., seeding [6], spraying [7], mowing [8], weeding [9,10], pruning [11,12], monitoring and inspection [13][14][15], and harvesting [16]. The existing literature has been reviewed and summarized by [17,18].…”

Section: Introductionmentioning

confidence: 99%

Conceptualization and Implementation of a Reconfigurable Unmanned Ground Vehicle for Emulated Agricultural Tasks

et al. 2022

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Small-to-medium sized systems able to perform multiple operations are a promising option for use in agricultural robotics. With this in mind, we present the conceptualization and implementation of a versatile and modular unmanned ground vehicle prototype, which is designed on top of a commercial wheeled mobile platform, in order to test and assess new devices, and motion planning and control algorithms for different Precision Agriculture applications. Considering monitoring, harvesting and spraying as target applications, the developed system utilizes different hardware modules, which are added on top of a mobile platform. Software modularity is realized using the Robot Operating System (ROS). Self- and ambient-awareness, including obstacle detection, are implemented at different levels. A novel extended Boundary Node Method is used for path planning and a modified Lookahead-based Line of Sight guidance algorithm is used for path following. A first experimental assessment of the system’s capabilities in an emulated orchard scenario is presented here. The results demonstrate good path-planning and path-following capabilities, including cases in which unknown obstacles are present.

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“…The Cowbot is an autonomous mower being developed to control weeds in pastures at the University of Minnesota West Central Research and Outreach Center in Morris, Minnesota ( Maini et al, 2022 ). The Cowbot uses the Global Positioning System ( GPS ) for navigation, with a GPS receiver on the Cowbot and a GPS receiver on a tripod in the pasture.…”

mentioning

confidence: 99%

Precision technologies to improve dairy grazing systems

2023

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Graphical Abstract Summary: Grazing dairy farmers may benefit from using on-farm precision technologies. However, the adoption of technology on grazing dairy farms is a challenge because of the lack of research-based information that addresses the accuracy and profitability of using technologies. In the future, pasture-based dairy farms are likely to rely on digital and automation technologies to improve animal health, reproduction, and well-being monitoring, pasture management, and labor productivity. Wearable animal technologies, remote sensing such as satellite imagery, unmanned aerial vehicles, virtual fencing, and automated animal herding, as well as ground-based sensing and automation, will provide potential solutions.

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Online Coverage Planning for an Autonomous Weed Mowing Robot With Curvature Constraints

Cited by 13 publications

References 25 publications

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Conceptualization and Implementation of a Reconfigurable Unmanned Ground Vehicle for Emulated Agricultural Tasks

Precision technologies to improve dairy grazing systems

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