Deep-Learning-Assisted Underwater 3D Tactile Tensegrity

Real-time Trajectory Planning and Tracking Control of Bionic Underwater Robot in Dynamic Environment

In this article, we study the trajectory planning and tracking control of a bionic underwater robot under multiple dynamic obstacles. We first introduce the design of the bionic leopard cabinet underwater robot developed in our lab. Then, we model the trajectory planning problem of the bionic underwater robot by combining its dynamics and physical constraints. Furthermore, we conduct global trajectory planning for bionic underwater robots based on the temporal-spatial Bezier curves. In addition, based on the improved proximal policy optimization, local dynamic obstacle avoidance trajectory replanning is carried out. In addition, we design the fuzzy proportional-integral-derivative controller for tracking control of the planned trajectory. Finally, the effectiveness of the real-time trajectory planning and tracking control method is verified by comparative simulation in dynamic environment and semiphysical simulation of UWSim. Among them, the real-time trajectory planning method has advantages in trajectory length, trajectory smoothness, and planning time. The error of trajectory tracking control method is controlled around 0.2 m.

Underwater Biomimetic Lateral Line Sensor Based on Triboelectric Nanogenerator for Dynamic Pressure Monitoring and Trajectory Perception

Developing desirable sensors is crucial for underwater perceptions and operations. The perceiving organs of marine creatures have greatly evolved to react accurately and promptly underwater. Inspired by the fish lateral line, this study proposes a triboelectric dynamic pressure sensor for underwater perception. The biomimetic lateral line sensor (BLLS) has high sensitivity to the disturbance amplitude/frequency, good adaptability to underwater environments and (relative) low cost. The sensors are deployed at the bottom of the test basin to perceive various moving objects, such as a robotic fish, robotic seal, etc. By analyzing the electrical signal of the sensor, the motion parameters of the objects passed over can be obtained. By monitoring signal variations across multiple sensors, the ability to sense different disturbance movement trajectories, including linear and angular trajectories, is achievable. The study will prove significant in forming an unconventional underwater perceiving method, which can back-up the sonic/optical sensors when are impaired in complex underwater environments.