Realistic Model Parameter Optimization: Shadow Robot Dexterous Hand Use-Case

• Type: Article in International Conference Proceedings Book
• Date: 2024

Authors

Correia, T (Author) Other; Ribeiro, FM (Author) Other; Pinto, VH (Author) FEUP

Conference proceedings International

Title: OPTIMIZATION, LEARNING ALGORITHMS AND APPLICATIONS, PT II, OL2A 2023

Pages: 244-255

3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A)

Ponta Delgada, PORTUGAL, SEP 27-29, 2023

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ISI Web of Knowledge - 0 Citations

Scopus

Other information

Authenticus ID: P-010-2XZ

DOI: 10.1007/978-3-031-53036-4_17

Abstract (EN): The notable expansion of technologies related to automated processes has been observed in recent years, largely driven by the significant advantages they provide across diverse industries. Concurrently, there has been a rise in simulation technologies aimed at replicating these complex systems. Nevertheless, in order to fully leverage the potential of these technologies, it is crucial to ensure the highest possible resemblance of simulations to real-world scenarios. In brief, this work consists of the development of a data acquisition and processing pipeline allowing a posterior search for the optimal physical parameters in MuJoCo simulator to obtain a more accurate simulation of a dexterous robotic hand. In the end, a Random Search optimization algorithm was used to validate this same pipeline.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12