Hierarchical Segmentation of Surfaces Embedded in R3 for Auto-Body Painting

Atkar, P.N.; Greenfield, Aaron; Conner, David C.; Choset, Howie

doi:10.1109/robot.2005.1570179

Cited by 15 publications

(16 citation statements)

References 13 publications

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“…It is worth noticing, however, that in this work the tackled problem is the uniform coverage problem, where the target surface not only needs to be completely covered but also the resulting paint deposition must meet certain uniformity requirements. To achieve uniform coverage, their proposed method takes a CAD model of the target automotive parts as input and segments their surface into topologically simple cells of similar curvature [Atkar et al, 2003[Atkar et al, , 2005a. Then, individual, optimal paintdeposition coverage paths in each cell are deter-mined.…”

Section: D Cellular Decompositionmentioning

confidence: 99%

A survey on coverage path planning for robotics

Galceran

Carreras

2013

Robotics and Autonomous Systems

1,149

602

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Coverage 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. This task is integral to many robotic applications, such as vacuum cleaning robots, painter robots, autonomous underwater vehicles creating image mosaics, demining robots, lawn mowers, automated harvesters, window cleaners and inspection of complex structures, just to name a few. A considerable body of research has addressed the CPP problem. However, no updated surveys on CPP reflecting recent advances in the field have been presented in the past ten years. In this paper, we present a review of the most successful CPP methods, focusing in the achievements made in the past decade. Furthermore, we discuss reported field applications of the described CPP methods. This work aims to become a starting point for researchers who are initiating their endeavors in CPP. Likewise, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works.

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Section: D Cellular Decompositionmentioning

confidence: 99%

A survey on coverage path planning for robotics

Galceran

Carreras

2013

Robotics and Autonomous Systems

1,149

602

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“…This trajectory is found in the work of Valente et al 6 using three solution options including tree-based search, heuristic-based search using wavefront planner and backtracking method and the pedestrian pocket algorithm that divides the grid cells into smaller cells to improve the computational cost. Another example of continuous coverage is illustrated in the studies of Atkar et al, 18,19 where an auto body painting planning method was developed to segment complex 3D models like a car into simple topological pieces (cells) and plan contiguous coverage paths over these segments minimizing geodesic curvature and providing uniform painting. The segmentation part of the algorithm is a cell decomposition performed using a slicing function that depends on surface geometry and topology to generate simple cells.…”

Section: Continuous Cppmentioning

confidence: 99%

A survey on inspecting structures using robotic systems

Almadhoun

Taha

Seneviratne

et al. 2016

International Journal of Advanced Robotic Systems

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Advancements in robotics and autonomous systems are being deployed nowadays in many application domains such as search and rescue, industrial automation, domestic services and healthcare. These systems are developed to tackle tasks in some of the most challenging, labour intensive and dangerous environments. Inspecting structures (e.g. bridges, buildings, ships, wind turbines and aircrafts) is considered a hard task for humans to perform and of critical importance since missing any details could affect the structure's performance and integrity. Additionally, structure inspection is time and resource intensive and should be performed as efficiently and accurately as possible. Inspecting various structures has been reported in the literature using different robotic platforms to: inspect difficult to reach areas and detect various types of faults and anomalies. Typically, inspection missions involve performing three main tasks: coverage path planning, shape, model or surface reconstruction and the actual inspection of the structure. Coverage path planning ensures the generation of an optimized path that guarantees the complete coverage of the structure of interest in order to gather highly accurate information to be used for shape/model reconstruction. This article aims to provide an overview of the recent work and breakthroughs in the field of coverage path planning and model reconstruction, with focus on 3D reconstruction, for the purpose of robotic inspection.

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“…Conner et al, [2,3,4] developed an automatic trajectory planning method for simple automotive surfaces. Their method is based on Gauss Bonnet Theorem generate the seed curve and its offset curves on a simple surface patch; these generated curves are used as paint gun trajectory.…”

Section: Introductionmentioning

confidence: 99%