As we know, for autonomous robots working in a complex underwater region, obstacle avoidance design will play an important role in underwater tasks. In this paper, a binocular-vision-based underwater obstacle avoidance mechanism is discussed and verified with our self-made Underwater Quadrocopter Vehicle. The proposed Underwater Quadrocopter Vehicle (UQV for short), like a quadrocopter drone working underwater, is a new kind of Autonomous Underwater Vehicle (AUV), which is equipped with four propellers along the vertical direction of the robotic body to adjust its body posture and two propellers arranged at the sides of the robotic body to provide propulsive and turning force. Moreover, an underwater binocular-vision-based obstacle positioning method is studied to measure an underwater spherical obstacle’s radius and its distance from the UQV. Due to its perfect ability of full-freedom underwater actions, the proposed UQV has obvious advantages such as a zero turning radius compared with existing torpedo-shaped AUVs. Therefore, one semicircle-curve-based obstacle avoidance path is planned on the basis of an obstacle’s coordinates. Practical pool experiments show that the proposed binocular vision can locate an underwater obstacle accurately, and the designed UQV has the ability to effectively avoid multiple obstacles along the predefined trajectory.

The mobility manager in the Internet of Underwater Things (IoUT) plays a major role in data acquisition. In this paper, one novel obstacle avoidance method based on fluid mechanics is discussed for autonomous underwater vehicle (AUV) in 3D IoUT. The proposed method utilizes ocean current characteristics simplified as stream-function to design an optimal 3D trajectory with an obstacle avoidance function. 3D stream-function is constructed for spherical and cylindrical obstructions in details. Theoretical analysis of 3D stream-function proves that traditional 2D stream-function can be extended to 3D IoUT space under specific conditions. One path deformation method based on virtual obstacle methodology is proposed to overcome the inherent hysteresis problem of the traditional stream-function based obstacle avoidance design. Moreover, we introduce an energy consumption model for AUV to prove that our obstacle avoidance algorithm can improve energy efficiency if actual ocean currents exist. Extensive simulation results verify that the proposed obstacle avoidance method has the characteristics of curve continuity and smoothness, enhanced obstacle avoidance effects, and high energy efficiency. Therefore, the proposed method meets the actual requirements of multi-obstacle avoidance path planning for AUV in IoUT.