Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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1.080 Topics available

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693.932 PEOPLE
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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2018Machining-based coverage path planning for automated structural inspection41citations
  • 2016Conformable eddy current array delivery2citations
  • 2014Automatic ultrasonic robotic array8citations

Places of action

Chart of shared publication
Morozov, Maxim
2 / 9 shared
Dobie, Gordon
3 / 21 shared
Macleod, Charles N.
3 / 45 shared
Pierce, Stephen
3 / 51 shared
Braumann, Johannes
1 / 1 shared
Riise, Jonathan
1 / 1 shared
Mineo, Carmelo
1 / 15 shared
Raude, Angélique
1 / 1 shared
Bolton, Gary
1 / 5 shared
Dalpé, Colombe
1 / 1 shared
Galbraith, Walter
1 / 2 shared
Gachagan, Anthony
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Chart of publication period
2018
2016
2014

Co-Authors (by relevance)

  • Morozov, Maxim
  • Dobie, Gordon
  • Macleod, Charles N.
  • Pierce, Stephen
  • Braumann, Johannes
  • Riise, Jonathan
  • Mineo, Carmelo
  • Raude, Angélique
  • Bolton, Gary
  • Dalpé, Colombe
  • Galbraith, Walter
  • Gachagan, Anthony
OrganizationsLocationPeople

article

Machining-based coverage path planning for automated structural inspection

  • Summan, Rahul
  • Morozov, Maxim
  • Dobie, Gordon
  • Macleod, Charles N.
  • Pierce, Stephen
Abstract

The automation of robotically delivered nondestructive evaluation inspection shares many aims with traditional manufacture machining. This paper presents a new hardware and software system for automated thickness mapping of large-scale areas, with multiple obstacles, by employing computer-aided drawing (CAD)/computer-aided manufacturing (CAM)-inspired path planning to implement control of a novel mobile robotic thickness mapping inspection vehicle. A custom postprocessor provides the necessary translation from CAM numeric code through robotic kinematic control to combine and automate the overall process. The generalized steps to implement this approach for any mobile robotic platform are presented herein and applied, in this instance, to a novel thickness mapping crawler. The inspection capabilities of the system were evaluated on an indoor mock-inspection scenario, within a motion tracking cell, to provide quantitative performance figures for positional accuracy. Multiple thickness defects simulating corrosion features on a steel sample plate were combined with obstacles to be avoided during the inspection. A minimum thickness mapping error of 0.21 mm and a mean path error of 4.41 mm were observed for a 2 m² carbon steel sample of 10-mm nominal thickness. The potential of this automated approach has benefits in terms of repeatability of area coverage, obstacle avoidance, and reduced path overlap, all of which directly lead to increased task efficiency and reduced inspection time of large structural assets.

Topics
  • Carbon
  • corrosion
  • steel
  • defect
  • drawing
  • collision-induced dissociation