4.6 Article

FEM-Based Exterior Workspace Boundary Estimation for Soft Robots via Optimization

Journal

IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 7, Issue 2, Pages 3672-3678

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2022.3147890

Keywords

Soft robotics; Finite element analysis; Robots; Estimation; End effectors; Actuators; Optimization; Soft robotics; workspace boundary; constrained optimization

Categories

Funding

  1. National Natural Science Foundation of China [62073081]
  2. Project of Department of Education of Guangdong Province [2019KZDXM037]
  3. Guangdong Hong Kong-Macao Joint Laboratory for IntelligentMicro-Nano Optoelectronic Technology [2020B1212030010]
  4. Project ROBOCOP [ANR-19-CE19]
  5. Project COSSEROOTS [ANR-20-CE33]
  6. Project Inventor (I-SITE ULNE, le programme d'Investissements d'Avenir, Metropole Europeenne de Lille, France)

Ask authors/readers for more resources

This study investigates the exterior workspace boundary of a soft robot, which is modeled using the Finite Element Method and controlled by bounded actuators. An optimization-based approach is implemented to estimate the boundary, showing its effectiveness through numerical simulations.
This letter investigates the exterior workspace boundary of a soft robot with a certain configuration controlled by equipped bounded actuators. To achieve this, we implement an optimization-based approach on the studied soft robot which has been modeled by the Finite Element Method (FEM). Finally, we provide numerical simulations of various configurations to demonstrate the validity of the suggested technique, which, in comparison to the conventional forward method, may considerably minimize the complexity of exterior workspace boundary estimation.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available