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Modeling and Control of a Spherical Robot in the CoppeliaSim Simulator.

Guelis MontenegroRoberto ChacónErnesto FabregasGonzalo GarciaKarla SchröderAlberto MarroquínSebastián Dormido-CantoGonzalo Farias
Published in: Sensors (Basel, Switzerland) (2022)
This article presents the development of a model of a spherical robot that rolls to move and has a single point of support with the surface. The model was developed in the CoppeliaSim simulator, which is a versatile tool for implementing this kind of experience. The model was tested under several scenarios and control goals (i.e., position control, path-following and formation control) with control strategies such as reinforcement learning, and Villela and IPC algorithms. The results of these approaches were compared using performance indexes to analyze the performance of the model under different scenarios. The model and examples with different control scenarios are available online.
Keyphrases
  • machine learning
  • public health
  • deep learning
  • global health