Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-Painting
This paper investigates the problem of collaborative robotic car-painting using a team of industrial manipulators that can be heterogeneous. Given the CAD model of the car, a collection of heterogeneous articulated robotic arms, and their corresponding fixed base positions on the factory floor/ceili...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9686367/ |
| _version_ | 1828136750335131648 |
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| author | K. Zbiss A. Kacem Mario Santillo A. Mohammadi |
| author_facet | K. Zbiss A. Kacem Mario Santillo A. Mohammadi |
| author_sort | K. Zbiss |
| collection | DOAJ |
| description | This paper investigates the problem of collaborative robotic car-painting using a team of industrial manipulators that can be heterogeneous. Given the CAD model of the car, a collection of heterogeneous articulated robotic arms, and their corresponding fixed base positions on the factory floor/ceiling, the objective is to generate a collection of joint trajectories for each robot in a computationally efficient manner such that the car body can be painted by the nozzles attached to the arms while collisions during the painting process are avoided. Our solution to this computationally intensive collaborative coverage path planning relies on decoupling the collision avoidance from the coverage path planning by exploiting the inherent two-dimensional structure of the problem. In particular, our algorithm relies on partitioning the reachable space of the forearms of these robots, projecting the resulting volumes of intersection on the sides and the top of the car body, and performing the coverage planning on the resulting projected volumes. Simulation results on several industrial arms that are collaboratively painting a Ford Motor Company F-150 truck demonstrate the effectiveness of our proposed solution. |
| first_indexed | 2024-04-11T18:09:12Z |
| format | Article |
| id | doaj.art-df562d1ea08045c883567cd0c7f98143 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T18:09:12Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-df562d1ea08045c883567cd0c7f981432022-12-22T04:10:14ZengIEEEIEEE Access2169-35362022-01-01109950995910.1109/ACCESS.2022.31446319686367Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-PaintingK. Zbiss0A. Kacem1https://orcid.org/0000-0002-6247-7248Mario Santillo2https://orcid.org/0000-0001-9152-4747A. Mohammadi3https://orcid.org/0000-0002-1089-3872Department of Electrical and Computer Engineering, University of Michigan--Dearborn, Dearborn, MI, USADepartment of Electrical and Computer Engineering, University of Michigan--Dearborn, Dearborn, MI, USAFord Motor Company, Dearborn, MI, USADepartment of Electrical and Computer Engineering, University of Michigan--Dearborn, Dearborn, MI, USAThis paper investigates the problem of collaborative robotic car-painting using a team of industrial manipulators that can be heterogeneous. Given the CAD model of the car, a collection of heterogeneous articulated robotic arms, and their corresponding fixed base positions on the factory floor/ceiling, the objective is to generate a collection of joint trajectories for each robot in a computationally efficient manner such that the car body can be painted by the nozzles attached to the arms while collisions during the painting process are avoided. Our solution to this computationally intensive collaborative coverage path planning relies on decoupling the collision avoidance from the coverage path planning by exploiting the inherent two-dimensional structure of the problem. In particular, our algorithm relies on partitioning the reachable space of the forearms of these robots, projecting the resulting volumes of intersection on the sides and the top of the car body, and performing the coverage planning on the resulting projected volumes. Simulation results on several industrial arms that are collaboratively painting a Ford Motor Company F-150 truck demonstrate the effectiveness of our proposed solution.https://ieeexplore.ieee.org/document/9686367/Computer integrated manufacturingcomputational geometrymulti-robot systemspath planning |
| spellingShingle | K. Zbiss A. Kacem Mario Santillo A. Mohammadi Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-Painting IEEE Access Computer integrated manufacturing computational geometry multi-robot systems path planning |
| title | Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-Painting |
| title_full | Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-Painting |
| title_fullStr | Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-Painting |
| title_full_unstemmed | Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-Painting |
| title_short | Automatic Collision-Free Trajectory Generation for Collaborative Robotic Car-Painting |
| title_sort | automatic collision free trajectory generation for collaborative robotic car painting |
| topic | Computer integrated manufacturing computational geometry multi-robot systems path planning |
| url | https://ieeexplore.ieee.org/document/9686367/ |
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