A Novel Visual Sensor Stabilization Platform for Robotic Sharks Based on Improved LADRC and Digital Image Algorithm

Abstract

Autonomous underwater missions require the construction of a stable visual sensing system. However, acquiring continuous steady image sequences is a very challenging task for bionic robotic fish due to their tight internal space and the inherent periodic disturbance caused by the tail beating. To solve this problem, this paper proposes a modified stabilization strategy that combines mechanical devices and digital image techniques to enhance the visual sensor stability and resist periodic disturbance. More specifically, an improved window function-based linear active disturbance rejection control (LADRC) was utilized for mechanical stabilization. Furthermore, a rapid algorithm with inertial measurement units (IMUs) was implemented for digital stabilization. The experiments regarding mechanical stabilization, digital stabilization, and target recognition on the experimental platform for simulating fishlike oscillations demonstrated the effectiveness of the proposed methods. The success of these experiments provides valuable insight into the construction of underwater visual sensing systems and also establishes a solid foundation for the visual applications for robotic fish in dynamic aquatic environments.

A Hierarchical Stabilization Control Method for a Three-Axis Gimbal Based on Sea–Sky-Line Detection

“…Therefore, it is noticeable that mechanical stabilization can effectively reduce the amplitude and velocity of large-angle motion and reduce the motion compensation and image compensation of electronic stabilization. In addition, since mechanical stabilization has been proven to be effective in improving image quality [ 25 ], it can also improve electronic stabilization. Better image quality is beneficial in improving the success rate of the following sea–sky-line detection.…”

Fuzzy active disturbance rejection control method for an omnidirectional mobile robot with MY3 wheel

“…But LADRC reduces part of the control performance while the parameters are simplified. Pan et al (2020) used LADRC based on an improved window function for the control of the bionic robotic fish, which effectively enhanced the stability and resisted periodic disturbance of the vision sensor. Chen et al (2018) used an improved LADRC for OMRs and introduced a tracking differentiator in the output to give the controller higher anti-disturbance capability and regulation efficiency.…”