Abstract
Industrial robot manipulators must work as fast as possible in order to increase the productivity. This goal could be achieved by increasing robots speed or/and optimizing the trajectories followed by robots while performing assembly, welding or similar tasks. In our contribution, we focus on the second aspect and we target the shortening of paths between task-points. In other words, the goal is to find the shorter traveled distance between different configurations in the coordinate space. In addition to the short distance goal, we aim as well to impose both IKM (Inverse Kinematic Model) and the relative position and orientation of the manipulator regarding the task-points. To this end, we propose an optimization method based on Genetics Algorithms. The method is validated via numerical and graphical simulation, where, results show that the total cycle time required to perform a spot-welding task of an industrial car-body by a 6-DOFs (Degree Of Freedoms) industrial manipulator was drastically reduced.
Original language | English |
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Title of host publication | ROSE 2014 - 2014 IEEE International Symposium on RObotic and SEnsors Environments, Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 112-117 |
Number of pages | 6 |
ISBN (Electronic) | 9781479949274 |
DOIs | |
Publication status | Published - 1 Jan 2014 |
Event | 2014 12th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2014 - Timisoara, Romania Duration: 16 Oct 2014 → 18 Oct 2014 |
Conference
Conference | 2014 12th IEEE International Symposium on Robotic and Sensors Environments, ROSE 2014 |
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Country/Territory | Romania |
City | Timisoara |
Period | 16/10/14 → 18/10/14 |
Keywords
- genetic algorithms
- Industrial manipulator
- optimization
ASJC Scopus subject areas
- Artificial Intelligence
- Human-Computer Interaction
- Electrical and Electronic Engineering