Title:
Robot Calligraphy using Pseudospectral Optimal Control and a Simulated Brush Model
Robot Calligraphy using Pseudospectral Optimal Control and a Simulated Brush Model
| dc.contributor.advisor | Dellaert, Frank | |
| dc.contributor.author | Chen, Jiaqi | |
| dc.contributor.department | Computer Science | |
| dc.contributor.department | Computer Science | |
| dc.date.accessioned | 2020-11-09T16:59:16Z | |
| dc.date.available | 2020-11-09T16:59:16Z | |
| dc.date.created | 2019-12 | |
| dc.date.issued | 2019-12 | |
| dc.date.submitted | December 2019 | |
| dc.date.updated | 2020-11-09T16:59:16Z | |
| dc.description.abstract | Chinese calligraphy is unique and has great artistic value but is difficult to master. In this paper, we make robots write calligraphy. Learning methods could teach robots to write, but may not be able to generalize to new characters. As such, we formulate the calligraphy writing problem as a trajectory optimization problem, and propose a new virtual brush model for simulating the dynamic writing process.Our optimization approach is taken from pseudospectral optimal control, where the proposed dynamic virtual brush model plays a key role in formulating the objective function to be optimized. We also propose a stroke-level optimization to achieve better performance compared to the character-level optimization proposed in previous work. Our methodology shows good performance in drawing aesthetically pleasing characters. | |
| dc.description.degree | Undergraduate | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/63855 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | Robotics | |
| dc.subject | Pseudospectral methods | |
| dc.subject | Chinese calligraphy | |
| dc.subject | Virtual brush | |
| dc.subject | Optimization | |
| dc.subject | Factor graphs | |
| dc.title | Robot Calligraphy using Pseudospectral Optimal Control and a Simulated Brush Model | |
| dc.type | Text | |
| dc.type.genre | Undergraduate Thesis | |
| dspace.entity.type | Publication | |
| local.contributor.advisor | Dellaert, Frank | |
| local.contributor.corporatename | College of Computing | |
| local.contributor.corporatename | School of Computer Science | |
| local.contributor.corporatename | Undergraduate Research Opportunities Program | |
| local.relation.ispartofseries | Undergraduate Research Option Theses | |
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| thesis.degree.level | Undergraduate |