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Home › Projects › Advanced Robotic Grinding System for Metal Parts

Advanced Robotic Grinding System for Metal Parts

Background

Grinding metal parts remains a repetitive and ergonomically unfriendly task that often generates inconsistent results. This project empowers American workers to transition from manual grinders into safer roles operating grinding robots through the development of an advanced robotic grinding system. The robotic grinding system uses model-based control and learning algorithms to account for uncertainties in its environment while using automated trajectory generation and 3D part model and identification of surface regions, creating consistent, high-quality results.

Objective

Increase the efficiency of grinding operations with decreased cost and better working conditions for human workers through the improvement of grinding robot algorithms.

Technical Approach

This project focused on the creation of an optimal work cell designed to facilitate efficiency in robotic grinding. The robot grinding system uses:

  • Automated trajectory generation, 3D part models, and the identification of surface regions that need grinding using sensors and efficient algorithms
  • Model-based control and learning algorithms to account for uncertainties

The components and algorithms generated for grinding robots will undergo comprehensive testing from stakeholders as part of the projects.

Participants

Texas A&M University, ITAMCO, University of Southern California, York Exponential


Project Type

Technology

Open Source/Open Architecture

Surface Finishing

Path Planning

Year Completed

2020

Project Team

ITAMCO

University of Southern California

York Exponential

Principle Investigator

Texas A&M University

ARM Institute

The ARM Institute is a Manufacturing Innovation Institute (MII) funded by the Office of the Secretary of Defense and is part of the Manufacturing USA® network.

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