Actuation of Elastic Tensegrity Knots
Event details
| Date | 24.06.2024 |
| Hour | 10:00 › 12:00 |
| Speaker | Liliane-Joy Dandy |
| Location | |
| Category | Conferences - Seminars |
EDIC candidacy exam
Exam president: Prof. Wenzel Jakob
Thesis advisor: Prof. Mark Pauly
Co-examiner: Prof. Josie Hughes
Abstract
Source Coding (or Compression) is one of the most fundamental problems in Information Theory. When the distribution of the source alphabet is known, Huffman coding achieves the entropy of the source alphabet (for finite alphabets) which is the fundamental limit. However, in most of the real life scenarios, the source alphabet is not known. In this case, it is not possible to have zero redundancy in one-shot. However, there are several Universal Compression algorithms for which the redundancy diminishes in the asymptotical case. In this work, I studied the background of Universal Compression along with the more recent Universal Coding techniques for any alphabet, including infinite and even unknown alphabets, that achieves diminishing redundancy. Moreover, I examined the performance analysis of some approaches that are specific to the large, possibly infinite, source alphabets.
Background papers
[1] Nico Pietroni, Marco Tarini, Amir Vaxman, Daniele Panozzo, and Paolo Cignoni. 2017. Position-based tensegrity design. ACM Trans. Graph. 36, 6, Article 172 (December 2017), 14 pages.
URL : https://dl.acm.org/doi/10.1145/3130800.3130809
[2] Michele Vidulis, Yingying Ren, Julian Panetta, Eitan Grinspun, and Mark Pauly. 2023. Computational Exploration of Multistable Elastic Knots. ACM Trans. Graph. 42, 4, Article 73 (August 2023), 16 pages.
URL : https://dl.acm.org/doi/abs/10.1145/3592399
[3] J. Bern, P. Banzet, R. Poranne and S. Coros. 2019. Trajectory optimization for cable-driven soft robot locomotion, Proc. Robot. Sci. Syst. (Jun. 2019 )
URL : https://www.roboticsproceedings.org/rss15/p52.pdf
Exam president: Prof. Wenzel Jakob
Thesis advisor: Prof. Mark Pauly
Co-examiner: Prof. Josie Hughes
Abstract
Source Coding (or Compression) is one of the most fundamental problems in Information Theory. When the distribution of the source alphabet is known, Huffman coding achieves the entropy of the source alphabet (for finite alphabets) which is the fundamental limit. However, in most of the real life scenarios, the source alphabet is not known. In this case, it is not possible to have zero redundancy in one-shot. However, there are several Universal Compression algorithms for which the redundancy diminishes in the asymptotical case. In this work, I studied the background of Universal Compression along with the more recent Universal Coding techniques for any alphabet, including infinite and even unknown alphabets, that achieves diminishing redundancy. Moreover, I examined the performance analysis of some approaches that are specific to the large, possibly infinite, source alphabets.
Background papers
[1] Nico Pietroni, Marco Tarini, Amir Vaxman, Daniele Panozzo, and Paolo Cignoni. 2017. Position-based tensegrity design. ACM Trans. Graph. 36, 6, Article 172 (December 2017), 14 pages.
URL : https://dl.acm.org/doi/10.1145/3130800.3130809
[2] Michele Vidulis, Yingying Ren, Julian Panetta, Eitan Grinspun, and Mark Pauly. 2023. Computational Exploration of Multistable Elastic Knots. ACM Trans. Graph. 42, 4, Article 73 (August 2023), 16 pages.
URL : https://dl.acm.org/doi/abs/10.1145/3592399
[3] J. Bern, P. Banzet, R. Poranne and S. Coros. 2019. Trajectory optimization for cable-driven soft robot locomotion, Proc. Robot. Sci. Syst. (Jun. 2019 )
URL : https://www.roboticsproceedings.org/rss15/p52.pdf
Practical information
- General public
- Free