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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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2023Development and Empirical Evaluation of a Biomimetic Autonomous Robotic Arm for Manipulating Objects with Diverse geometries1citations

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Chart of shared publication
Mohanraj, A. P.
1 / 1 shared
Venkatesan, S.
1 / 9 shared
Nijanthan, V.
1 / 1 shared
Yokeshkanna, K.
1 / 1 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Mohanraj, A. P.
  • Venkatesan, S.
  • Nijanthan, V.
  • Yokeshkanna, K.
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article

Development and Empirical Evaluation of a Biomimetic Autonomous Robotic Arm for Manipulating Objects with Diverse geometries

  • Mohanraj, A. P.
  • Venkatesan, S.
  • Veerabarath, M. P.
  • Nijanthan, V.
  • Yokeshkanna, K.
Abstract

<jats:title>Abstract</jats:title><jats:p>This paper discusses the design and development of a biomimetic robotic arm, elaborating on the experiments conducted with the developed arm to handle objects of diverse geometries, as well as evaluating its agility during grasping tasks. When automating fruit harvesting, it is crucial to minimize damage to leaves, as they play an essential role in the photosynthesis process. Thus, a versatile prehensile design is imperative for grasping fruits with various shapes. Existing technologies for harvesting fruit meant for processing are limited to soft, fresh fruit due to the risk of mechanical damage. As an alternative, a robotic system that emulates human fruit picking can improve fruit quality while maintaining efficiency. Consequently, a robotic hand with deformable fingers inspired by the human arm is developed. The robotic system must also be cost-effective. A single-gear motor is utilized to control the arm’s functions and ensure agile responsiveness when grasping objects with different shapes, incorporating a self-adaptive mechanism. During the development process, several grasping tests are conducted to evaluate the arm’s ability to handle basic shape primitives such as spheres and cylinders. The goal is to offer an alternative to manual fruit picking by creating a system capable of identifying, locating, and detaching fruit without causing damage to the fruit or tree. The robot is also equipped with A. In technology such as object detection and manipulation, the model is trained using a convolutional neural network for grasping the objects with appropriate pressures.</jats:p>

Topics
  • impedance spectroscopy
  • experiment