Uniform Coverage of Automotive Surface Patches

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

doi:10.1177/0278364905059058

Cited by 144 publications

(73 citation statements)

References 17 publications

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“…Coverage has also been addressed in the field of spray painting automotive parts. Atkar et al [1] show how simple automotive parts like convex bent sheets can be covered such that the resultant paint deposition on the target surface achieves acceptable uniformity. In these applications however, the robot does not operate on the surface.…”

Section: Related Workmentioning

confidence: 99%

Null space optimization for effective coverage of 3D surfaces using redundant manipulators

Hess

Tipaldi

Burgard

2012

2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-In this paper we consider the problem of null space minimization in coverage path planning of 3D surfaces for redundant manipulators. Existing coverage solutions only focus on Euclidean cost functions and often return suboptimal paths with respect to the joint space. In the approach described here, we explicitly consider the null space by treating different inverse kinematics solutions as individual nodes in a graph and model the problem as a generalized traveling salesman problem (GTSP). The GTSP is a generalization of the TSP where the nodes of the graph are subdivided into clusters and at least one node in each cluster needs to be visited. We evaluate our approach using a PR2 robot and complex objects. Our results demonstrate that our method outperforms Euclidean coverage algorithms in terms of manipulation effort and completion time.

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Section: Related Workmentioning

confidence: 99%

Null space optimization for effective coverage of 3D surfaces using redundant manipulators

Hess

Tipaldi

Burgard

2012

2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…This task is integral to many robotic applications, such as vacuum cleaning robots [Yasutomi et al, 1988], painter robots [Atkar et al, 2005b], autonomous underwater vehicles creating image mosaics [Hert et al, 1996], demining robots [Gage, 1994;Najjaran and Kircanski, 2000;Acar et al, 2003], lawn mowers [Cao et al, 1988;Bosse et al, 2007], automated harvesters Stentz, 1996, 1997] window cleaners [Farsi et al, 1994] and inspection of complex underwater structures [Englot and Hover, 2012], just to name a few.…”

Section: Introductionmentioning

confidence: 99%

A survey on coverage path planning for robotics

Galceran

Carreras

2013

Robotics and Autonomous Systems

1,202

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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“…However, the paint deposition model of the electrostatic rotating bell atomizer is significantly different from the model presented earlier. Conner et al [6][7][8] proposed a highly accurate double Gaussians paint deposition model based on an ESRB spray gun, by using an offset 1-D Gaussian revolved about the axis of the spray gun, and a 2-D Gaussian centered at the origin of the deposition model plane to capture the shape of the paint distribution. In this article, a new practical ESRB cumulative rate model of painting is derived, and the experimental study on painting is carried out after using the experimental method to obtain the radial thickness profile function of the spatial painting distribution of static spray.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Optimization of Electrostatic Spray Painting Robots on Curved Surface

et al. 2017

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Abstract:In this paper, a new practical electrostatic rotating bell (ESRB) cumulative rate model of painting is derived, and an experimental study on painting is carried out. First, the experimental method is used to obtain the radial thickness profile function of the spatial paint distribution of static spray. Then, a spatial trajectory-planning scheme for a spray-painting robot based on a rectangular model is presented. This method designs the spatial path of the spray-painting robot by using the cuboid model method after the optimal value is taken as the width d of the overlapping area of the two spray-painting strokes in the plane. The experimental results illustrate that the paint thickness basically meets the requirements, and the experimental results verify the effectiveness of the trajectory optimization method.

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Uniform Coverage of Automotive Surface Patches

Abstract: Abstract

Cited by 144 publications

References 17 publications

Null space optimization for effective coverage of 3D surfaces using redundant manipulators

Null space optimization for effective coverage of 3D surfaces using redundant manipulators

A survey on coverage path planning for robotics

Trajectory Optimization of Electrostatic Spray Painting Robots on Curved Surface

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