Logo image
Development of a Numerical Model of a Bio-Inspired Sea Lion Robot
Journal article   Open access   Peer reviewed

Development of a Numerical Model of a Bio-Inspired Sea Lion Robot

Shraman Kadapa, Nicholas Marcouiller, Anthony C. Drago, James L. Tangorra and Harry G. Kwatny
Biomimetics (Basel, Switzerland), v 10(11), 772
14 Nov 2025
PMID: 41294444
url
https://doi.org/10.3390/biomimetics10110772View
Published, Version of Record (VoR)Open Access Discount via Drexel Libraries Read and Publish Program 2025CC BY V4.0 Open

Abstract

modeling simulation marine hydrodynamics bio-inspired robotics dynamics computational fluid dynamics
There is a growing demand for underwater robots to support offshore tasks such as exploration, environmental monitoring, and critical underwater missions. To enhance the performance of these systems, researchers are increasingly turning to biological inspiration to develop robots that understand and adapt the swimming strategies of aquatic animals. Numerical modeling plays a critical role in evaluating and improving the performance of these complex, multi-body robotic systems. However, developing accurate models for multi-body robots that swim freely in three dimensions remains a significant challenge. This study presents the development and validation of a numerical model of a bio-inspired California sea lion (Zalophus californianus) robot. The model was developed to simulate, analyze, and visualize the robot’s body motions in water. The equations of motion were derived in closed form using the Euler–Poincaré formulation, offering advantages for control and stability analysis. Hydrodynamic coefficients essential for estimating fluid forces were computed using computational fluid dynamics (CFD) and strip theory and further refined using a genetic algorithm to reduce the sim-to-real gap. The model demonstrated strong agreement with experiments, accurately predicting the translation and orientation of the robot. This framework provides a validated foundation for simulation, control, and optimization of bio-inspired multi-body systems.

Metrics

16 Record Views

Details

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Web of Science research areas
Engineering, Multidisciplinary
Materials Science, Biomaterials
Logo image