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PARAMETER TUNING OF ADDICTIVE MANUFACTURING CONTINUUM FLEXIBLE MANIPULATOR SIMULATION

PARAMETER TUNING OF ADDICTIVE MANUFACTURING CONTINUUM FLEXIBLE MANIPULATOR SIMULATION

Novaes, Luis V. ; Matos, Victor S. ; Mendes, João V. ; Silva, Lucas C. ;

Full article:

This work presents the process to simulate accurately a continuum flexible manipulator produced through addictive manufacturing (AM). A manipulator is an element capable of interaction with the space around it, a common example is a rigid robotic arm. The Finite Element Method (FEM) software adopted was the SOFA framework. The tuning process consists of adjusting the simulation parameters to achieve sufficient accuracy in the manipulator movement in space. A real manipulator was used, based on known input value application, the space position was measured, and compared with the simulated version. The simulated version achieved more than 240 % of improvement as compared to the nominal material parameters. The 3D positioning for steady-state study case reached 10 % of distance error, and a parameters surface was mapped to better understand the tunning process.

Full article:

This work presents the process to simulate accurately a continuum flexible manipulator produced through addictive manufacturing (AM). A manipulator is an element capable of interaction with the space around it, a common example is a rigid robotic arm. The Finite Element Method (FEM) software adopted was the SOFA framework. The tuning process consists of adjusting the simulation parameters to achieve sufficient accuracy in the manipulator movement in space. A real manipulator was used, based on known input value application, the space position was measured, and compared with the simulated version. The simulated version achieved more than 240 % of improvement as compared to the nominal material parameters. The 3D positioning for steady-state study case reached 10 % of distance error, and a parameters surface was mapped to better understand the tunning process.

Palavras-chave: continuum manipulator, simulation, SOFA, parameters calibration,

Palavras-chave: continuum manipulator, simulation, SOFA, parameters calibration,

DOI: 10.5151/siintec2023-305940

Referências bibliográficas
  • [1] "EL-ATAB, Nazek et al. Soft actuators for soft robotic applications: A review. Advanced Intelligent Systems, v. 2, n. 10, p. 2000128, 2020.
  • [2] GEORGE THURUTHEL, Thomas et al. Control strategies for soft robotic manipulators: A survey. Soft robotics, v. 5, n. 2, p. 149-163, 2018.
  • [3] COEVOET, Eulalie et al. Software toolkit for modeling, simulation, and control of soft robots. Advanced Robotics, v. 31, n. 22, p. 1208-1224, 2017.
  • [4] CANGAN, Barnabas Gavin et al. Model-based disturbance estimation for a fiber-reinforced soft manipulator using orientation sensing. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2022. p. 9424-9430.
  • [5] FAURE, François et al. Sofa: A multi-model framework for interactive physical simulation. Soft tissue biomechanical modeling for computer assisted surgery, p. 283-321, 2012.
  • [6] ROELS, Ellen et al. Additive manufacturing for self-healing soft robots. Soft robotics, v. 7, n. 6, p. 711-723, 2020.
  • [7] QUEIROZ, Rafael Santana et al. A Literature Review of Additive Manufacturing in the Fabrication of Soft Robots: Main Techniques, Applications, and Related Industrial-Sized Machines. JOURNAL OF BIOENGINEERING, TECHNOLOGIES AND HEALTH, v. 6, n. 1, p. 91-97, 2023.
  • [8] ZHANG, Zhongkai. Vision-based calibration, position control and force sensing for soft robots. 2019. Tese de Doutorado. Université de Lille.
  • [9] CURKOVIC, P.; CUBRIC, G. Fused Deposition Modelling for 3D printing of Soft Anthropomorphic Actuators. International journal of simulation modelling, v. 20, n. 2, p. 12, 2021.
  • [10] FERRENTINO, Pasquale et al. Finite Element Analysis-Based Soft Robotic Modeling: Simulating a Soft Actuator in SOFA. IEEE Robotics & Automation Magazine, 2023.
  • [11] DURIEZ, Christian et al. Framework for online simulation of soft robots with optimization-based inverse model. In: 2016 IEEE international conference on simulation, modeling, and programming for autonomous robots (SIMPAR). IEEE, 2016. p. 111-118.
  • [12] 14 GARRIDO-JURADO, Sergio et al. Automatic generation and detection of highly reliable fiducial markers under occlusion. Pattern Recognition, v. 47, n. 6, p. 2280-2292, 2014.
  • [13] 10 HP. HP 3D Printing materials for the HP Jet Fusion 5200 Series 3D Printing Solution. [Online]. Available at: https://h20195.www2.hp.com/v2/GetDocument.aspx?docna
  • [14] me=4AA7-7084ENW. Accessed on: Jul. 26, 2023.
  • [15] 11 Poisson's Ratio - Polymer Database. Available at: https://polymerdatabase.com/poly
  • [16] mer%20physics/Poisson%20Table.html. Access on: Jul. 26, 2023."
Como citar:

Novaes, Luis V. ; Matos, Victor S. ; Mendes, João V. ; Silva, Lucas C. ; "PARAMETER TUNING OF ADDICTIVE MANUFACTURING CONTINUUM FLEXIBLE MANIPULATOR SIMULATION ", p. 251-259 . In: . São Paulo: Blucher, 2023.
ISSN 2357-7592, DOI 10.5151/siintec2023-305940

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