Binocular-Vision-Based Obstacle Avoidance Design and Experiments Verification for Underwater Quadrocopter Vehicle

Abstract

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.

Communication-Aware Motion Planning of AUV in Obstacle-Dense Environment: A Binocular Vision-Based Deep Learning Method

“…3) Comparison With the Single Horizontal Cameras: As mentioned above, this paper jointly employs the horizontal and vertical parallax angles to achieve collision-free motion planning, which can improve the flexibility of obstacle avoidance. To verify its merit, we consider the following two cases: 1) The horizontal parallax angle is adopted to achieve obstacle avoidance, e.g., the solution in [13]; 2) The horizontal and vertical parallax angles are jointly adopted to achieve the obstacle avoidance, i.e., the solution in this paper. Besides that, it is set that three column obstacles block the way of AUV.…”

“…Of note, the former category is traditionally the primary way for long-distance detection of AUV. However, sonar has low resolution ability due to the underwater reverberation noise and multi-path fading effect [13], which may lead to the performance degradation of collision avoidance, especially in obstacle-dense environments. For example, the sidescan sonar with a low frequency can only have low-quality acoustic data, due to the speckle noises caused by acoustic wave interferences [14], [15].…”

A Systematic Stereo Camera Calibration Strategy: Leveraging Latin Hypercube Sampling and 2k Full-Factorial Design of Experiment Methods

“…Binocular or stereo vision, used in diverse areas like autonomous driving [1,2], robot navigation [3,4], 3D reconstruction [5][6][7], and industrial inspection [8,9], employs two identical cameras to capture two images of the same target from different vantage points. The disparity between these images enables 3D reconstruction and measurement, the accuracy of which is heavily dependent on the precision of the camera calibration and stereo matching methods, thus making these processes key research subjects in stereo vision.…”