桨驱动微型自主水下机器人系统设计

自主水下潜航器（AUV），又称自主水下机器人，是指在无人干预的情况下，能够独立完成自主导航、自主避障、自主作业等任务的水下机器人。自主水下机器人在军事侦察、自然资源勘探、救助打捞、管道及船体探伤等领域发挥着重要作用。目前，国内外关于自主水下机器人研究的工作，一部分集中在较大型的航行器，其丰富的传感器可以极大提高机器人智能化水平，但体积较大无法探测狭窄场景；另一部分集中在微小型仿生机器人，由于智能化程度较低不能满足复杂场景的探测需求。在一些复杂而狭窄的探测场景中，自主水下机器人需要同时具备体积小、自主性高、感知力强、机动性好的性能特点。
针对这一应用需求，本文设计了一个基于螺旋桨驱动的微型自主水下机器人，以实现在狭窄复杂场景的高机动自主探测侦察。机器人集成了高性能处理器树莓派CM4 模块、STM32F4 系列核心处理器、高清相机模块、高精度惯性测量单元（IMU）、水深传感器等，以提高数据处理和环境感知能力。通过IMU、水深传感器实时获取机器人的姿态和位置信息，处理器控制六个螺旋桨的运动状态，实现空间六自由度运动。高清相机捕获环境数据，处理器通过图像处理、目标识别算法处理数据，进而实现环境探测并为机器人运动提供参考。高度集成的电路设计和外壳设计，确保了整机的最大长度为12.88 厘米，最大直径为5.62 厘米，以便于适用更多狭小
探测场景；主处理器、协处理器配合的双系统设计，确保了高效的数据处理和稳定的姿态控制；丰富的传感器集成、高性能处理器选用和多种图像处理算法的开发，为目标跟踪和识别提供了更多可能性。经过水下实验和管道测试，本文设计的自主水下机器人在狭窄通道中显示出优越的运动性能和目标探测能力。

Autonomous underwater vehicles (AUVs), also known as autonomous underwater robots, are underwater robots that can independently perform tasks such as autonomous navigation, autonomous obstacle avoidance, and autonomous operations without human intervention. Autonomous underwater robots play an important role in military reconnaissance, natural resource exploration, rescue and salvage, pipeline and ship hull probing, etc. At present, some work on autonomous underwater robots focuses on larger navigators, where sensors can greatly improve the intelligence of the robot, but they cannot detect narrow scenes with the larger size; another work focus on micro and small bionic robots, which cannot meet the detection needs of complex scenes due to the lower intelligence. In some complex and narrow detection scenes, autonomous underwater robots need to have the performance characteristics of small size, high autonomy, strong perception and good mobility at the same time.

For this application requirement, this thesis designs a propeller-driven miniature autonomous underwater robot to achieve highly mobile autonomous detection and reconnaissance in narrow and complex scenes. The robot integrates a high-performance processor Raspberry Pi CM4 module, STM32F4 series core processor, high-definition camera module, high-precision inertial measurement unit (IMU), and bathymetry sensor to improve data processing and environment sensing capability. The IMU and water depth sensor acquire the robot's attitude and position information in real time, and the processor controls the motion state of the six propellers to achieve six degrees of freedom movement in space. The HD camera captures environmental data, and the processor processes the data through image processing and target recognition algorithms to achieve environmental detection and provide reference for robot motion. The highly integrated circuit design and housing design ensure that the robot has a maximum length of 12.88 cm and a maximum diameter of 5.62 cm to allow for more narrow detection scenarios; the dual system design with main processor and co-processor ensures efficient data processing and stable attitude control; the rich sensor integration, the selection of high-performance processor and the development of various image processing algorithms provide more possibilities for target tracking and identification. After underwater experiments and pipeline tests, the autonomous underwater robot in this thesis has shown superior motion performance and target detection capability through narrow passages.

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