Coverage Path Planning and Precise Localization for Autonomous Lawn Mowers

Höffmann, M.; Clemens, Joachim; Stronzek‐Pfeifer, David; Simonelli, Ruggero; Serov, Andreas; Schettino, Sven; Runge, Margareta; Schill, Kerstin; Büskens, Christof

doi:10.1109/irc55401.2022.00046

Cited by 4 publications

(5 citation statements)

References 23 publications

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“…The path points of the piecewise linear interregion path L are employed as control points, or the path is further discretized to have an equal step size. We then solve a nonlinear optimization problem to compute the optimal weights w. Denoting the squared Euclidean distance between a point on the NURBS curve C w (u) and the closest point on L as dist 2 w (L, u) ∈ R for u ∈ D, and representing the corresponding curvature in this point of the NURBS curve as κ w (u), the formulation of the nonlinear optimization problem is as follows:…”

Section: Smoothing Inter-region Paths Using Nurbs Curvesmentioning

confidence: 99%

“…The complete coverage path planning (CCPP) problem is a critical aspect of industrial motion planning, involving the efficient traversal of every single point within a designated area. Finding an optimal solution to this problem holds high significance across various domains and has become particularly crucial in the realm of mobile robot applications, including agriculture, autonomous cleaning [1], lawn mowing [2], structural inspection [3], and surveillance [4]. Additionally, CCPP has found its place in industrial and treatment applications such as milling [5], laser cleaning [6], disinfection [7], and spray painting [8].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints

Höffmann,

Patel,

Büskens

2023

Agriculture

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Complete coverage path planning (CCPP) is vital in mobile robot applications. Optimizing CCPP is particularly significant in precision agriculture, where it enhances resource utilization, reduces soil compaction, and boosts crop yields. This work offers a comprehensive approach to CCPP for agricultural vehicles with curvature constraints. Our methodology comprises four key stages. First, it decomposes complex agricultural areas into simpler cells, each equipped with guidance tracks, forming a fixed track system. The subsequent route planning and smooth path planning stages compute a path that adheres to path constraints, optimally traverses the cells, and aligns with the track system. We use the generalized traveling salesman problem (GTSP) to determine the optimal traversing sequence. Additionally, we introduce an algorithm for calculating paths that are both smooth and curvature-constrained within individual cells, as well as paths that enable seamless transitions between cells, resulting in a smooth, curvature-constraint coverage path. Our modular approach allows method flexibility at each step. We evaluate our method on real agricultural fields, demonstrating its effectiveness in minimizing path length, ensuring efficient coverage, and adhering to curvature constraints. This work establishes a strong foundation for precise and efficient agricultural coverage path planning, with potential for further real-world applications and enhancements.

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Section: Smoothing Inter-region Paths Using Nurbs Curvesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints

Höffmann,

Patel,

Büskens

2023

Agriculture

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“…For given convex polygon cP 1 = p 1 p 2 p 3 p 10 p 11 p 12 , search function tp = SearchSH (cP 1 ) returns tp = [10,1,12]. This means that the vertical height h 10M from p 10 to the edge p 1 p 12 is the shortest one among h iM , i = 1, 2, 3, 10, 11, 12.…”

Section: A Cbspsa For Cp(c P 1 )mentioning

confidence: 99%

“…C OVERAGE path planning (CPP) is the task of determining a path that passes over all points of an area or volume of interest while avoiding obstacles [2]- [5]. This CPP problem arises in various practical applications, such as vacuum cleaning robot [6]- [8], lawn mower [1], [9], [10], demining robot [11], [12], automated harvester [13], [14], and NC pocket machine [9], [15], [16]. These applications further can be classified into two types [1]: lawn mowing problem [9]- [14] and milling problem [6], [7], [15], [16].…”

Section: Introductionmentioning

confidence: 99%

Full Coverage of Confined Irregular Polygon Area for Marine Survey

Li,

Kang,

Kim

et al. 2023

IEEE Access

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This paper considers the coverage path planning (CPP) problem for marine surveys, where the survey vehicles' movements are confined in the irregular polygon search area. So this is a sort of milling problem [1] with the minimum number of turns in order for improvement of the acquired sonar image quality. For this purpose, this paper proposes a novel method called CbSPSA (calculation based shortest path search algorithm). Especially in the irregular corner area, this algorithm can easily calculate a kind of shortest path for its full coverage of this irregular area. For any given polygon, it can always be partitioned into convex polygon(s). In this paper, we only consider the case where these divided convex polygons are all connected one by one. In this case, the shortest path with minimum turns in each convex polygon can be easily searched by CbSPSA. And further by simply linking all of these pieces, the total coverage path for any given polygon area can be constructed. On the other hand, for a given polygon, usually there are several different cases of partition. Among the searched coverage paths for each of these different partitions, the final optimal coverage path is determined through a predefined criteria. Numerical simulation and analyses are carried out to demonstrate the effectiveness of the proposed method.INDEX TERMS Coverage path planning (CPP), marine surveys, lawn mowing, milling, convex polygon.

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“…The Complete Coverage Path Planning (CCPP) problem arises when dealing with mobile agents engaged in operations that require an efficient route traversing every single point in a given area of interest. Classified as a subfield of industrial motion planning, solving the CCPP problem in an optimal way is highly relevant for a large number of domains, ranging from mobile robot applications such as agriculture, autonomous cleaning (Ntawumenyikizaba et al, 2012), autonomous lawn mowing (Höffmann, Clemens, et al, 2022), structural inspection (Galceran et al, 2015), and surveillance (Basilico & Carpin, 2015), to industrial or treatment applications such as milling (Kalburgi et al, 2020), laser cleaning (Ye et al, 2020) or spray painting (Kiemel et al, 2019). The use of CCPP techniques is especially essential in precision agriculture using unmanned ground vehicles or the so‐called auto‐guidance devices, as they facilitate efficient use of resources such as fuel, fertilizers, and land, reduce soil compaction, and ultimately increase yields.…”

Section: Introductionmentioning

confidence: 99%

Optimal guidance track generation for precision agriculture: A review of coverage path planning techniques

Höffmann,

Patel,

Büskens

2024

Journal of Field Robotics

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The Complete Coverage Path Planning (CCPP) problem is a subfield of industrial motion planning that has applications in various domains, ranging from mobile robotics to treatment applications. Especially in precision agriculture with a high level of automation, the use of CCPP techniques is essential for efficient resource utilization, reduced soil compaction, and increased yields. This paper reviews the CCPP problem in the context of machines operating in agricultural fields and proposes a methodological approach consisting of three steps: Generating the Guidance Tracks (i.e., the track system along which the path should be oriented), determining the traversing sequence through these tracks, and planning a smooth and drivable path. This paper provides an in‐depth review of optimization‐based approaches that deal with the first step, the generation of the guidance track system. Thereby, a comprehensive and pedagogical approach for the generation of guidance tracks for arbitrarily shaped two‐dimensional regions of interest is provided, along with an overview and detailed elaboration on different exact cellular decomposition techniques found in literature. Furthermore, cost functions are outlined for the different approaches presented in this work, which are utilized to generate optimal guidance tracks. Finally, this survey serves as an introductory guide for research and practitioners to solve the CCPP problem effectively and efficiently.

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Coverage Path Planning and Precise Localization for Autonomous Lawn Mowers

Cited by 4 publications

References 23 publications

Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints

Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints

Full Coverage of Confined Irregular Polygon Area for Marine Survey

Optimal guidance track generation for precision agriculture: A review of coverage path planning techniques

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