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Enhancing maneuverability of bioinspired aquatic soft robots via multistable mechanisms

Grant number: 22/07119-2
Support Opportunities:Regular Research Grants
Duration: October 01, 2022 - September 30, 2024
Field of knowledge:Engineering - Mechanical Engineering - Mechanical Engineering Design
Principal Investigator:Maira Martins da Silva
Grantee:Maira Martins da Silva
Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

There is an ever-increasing demand for underwater inspections to assess environmental risk and extreme events. During these inspections, devices can acquire data that can enrich these analyses. Underwater robots can accomplish this task. However, they should move in unstructured environments, which require maneuverability and energy efficiency. This work proposes designing a bioinspired soft robotic system capable of mimicking undulatory and oscillatory movements. Recently, the research team responsible for this project developed a carbon-fiber structure actuated by Macro Fiber Composite (MFC) to perform such movements. However, due to its construction, the maneuverability of this structure is limited. A promising strategy to improve the ability to perform maneuvers is multi-stable mechanisms. These mechanisms, which can be 3D printed, could be responsible for controlling the direction in which the propulsion will act. A robotic system composed of multi-stable mechanisms and structures driven by MFC actuator pairs will be designed through numerical simulations and experimentally validated. For this system, a motion planning strategy based on Model Predictive Control (MPC) approach will be investigated. The robotic system should pursue a target sensed by the camera through a closed-loop control strategy based on the MPC approach. Contributions in the field of soft robotics and underwater robotic applications are expected. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SESTITO, GUILHERME SERPA; ALVAREZ-BRICENO, RICARDO; RIBATSKI, GHERHARDT; DA SILVA, MAIRA MARTINS; RODRIGUES DE OLIVEIRA, LEOPOLDO PISANELLI. Vibration-based multiphase-flow pattern classification via machine learning techniques. FLOW MEASUREMENT AND INSTRUMENTATION, v. 89, p. 12-pg., . (22/07119-2, 10/02198-4)
BARBOSA, ARTHUR SILVA; DA SILVA, MAIRA MARTINS. Macro Fiber Composite-Actuated Soft Robotic Fish: A Gray Box Model-Predictive Motion Planning Strategy Under Limited Actuation. SOFT ROBOTICS, v. N/A, p. 11-pg., . (22/07119-2, 18/15894-0)

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