Collaborative obstacle avoidance algorithm of multiple bionic snake robots in fluid based on IB-LBM.

Area of Science:

• Robotics
• Fluid Dynamics
• Computational Science

Background:

• Coordinated movement and obstacle avoidance are critical for multi-robot systems in complex environments.
• Traditional methods struggle with the non-linear dynamics and complex boundary conditions inherent in fluid simulations involving robots.

Purpose of the Study:

• To develop and validate a collaborative obstacle avoidance algorithm for multiple bionic snake robots operating in a fluid medium.
• To enhance the simulation accuracy and efficiency of multi-robot systems in dynamic fluid environments.

Main Methods:

• Utilized the Lattice Boltzmann Method (LBM) to establish a non-linear fluid model capable of simulating random motion beyond classical Navier-Stokes limitations.
• Employed the Immersed Boundary Method (IBM) to create a force source boundary model for multiple bionic snake robots, improving computational efficiency and stability.
• Implemented an improved Serpenoid curve function and specific forces to enable collaborative, non-colliding obstacle avoidance among robots.

Main Results:

• The proposed algorithm successfully enabled multiple bionic snake robots to avoid various obstacles in fluid.
• Simulation experiments demonstrated the robots' ability to navigate collaboratively and avoid collisions.
• The method exhibited high parallelism and effectively handled complex boundary conditions, reducing computational grid conversion.

Conclusions:

• The developed IB-LBM based algorithm is effective for collaborative obstacle avoidance in multi-bionic snake robot systems operating in fluids.
• The approach offers a robust and efficient solution for simulating complex robot-fluid interactions and coordinated behaviors.