Abstract / Description of output
Dynamic System Identification approaches usually heavily rely on evolutionary and gradient-based optimisation techniques to produce optimal excitation trajectories for determining the physical parameters of robot platforms. Current optimisation techniques tend to generate single trajectories. This is expensive, and intractable for longer trajectories, thus limiting their efficacy for system identification. We propose to tackle this issue by using multiple shorter cyclic trajectories, which can be generated in parallel, and subsequently combined together to achieve the same effect as a longer trajectory. Crucially, we show how to scale this approach even further by increasing the generation speed and quality of the dataset through the use of generative adversarial network (GAN) based architectures to produce large databases of valid and diverse excitation trajectories. To the best of our knowledge, this is the first robotics work to explore system identification with multiple cyclic trajectories and to develop GAN-based techniques for scaleably producing excitation trajectories that are diverse in both control parameter and inertial parameter spaces. We show that our approach dramatically accelerates trajectory optimisation, while simultaneously providing more accurate system identification than the conventional approach.
Original language | English |
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Title of host publication | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 7109 - 7115 |
Number of pages | 7 |
ISBN (Electronic) | 978-1-7281-6212-6 |
ISBN (Print) | 978-1-7281-6213-3 |
DOIs | |
Publication status | Published - 10 Feb 2021 |
Event | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, United States Duration: 25 Oct 2020 → 29 Oct 2020 https://www.iros2020.org/index.html |
Publication series
Name | |
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Publisher | IEEE |
ISSN (Print) | 2153-0858 |
ISSN (Electronic) | 2153-0866 |
Conference
Conference | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems |
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Abbreviated title | IROS 2020 |
Country/Territory | United States |
City | Las Vegas |
Period | 25/10/20 → 29/10/20 |
Internet address |