电子学报2026，Vol.54Issue(1)：141-152,12.DOI:10.12263/DZXB.20250753
高精度高速度低算力的AUV水下导引光学定位方法
High-Precision,High-Speed,and Low-Computing-Power AUV Optical Positioning Method
摘要
Abstract
After performing long-duration ocean exploration and other operational tasks,autonomous underwater vehi-cles(AUV)must return to a recovery station for energy replenishment and data transmission.During the AUV's terminal re-covery phase,the positioning accuracy and speed of its positioning system directly influence the success rate of AUV guid-ance.Among current guidance technologies,acoustic guidance methods offer long operating ranges but their positioning ac-curacy struggles to meet close-range docking requirements;while vision-based guidance methods offer higher accuracy,they are susceptible to interference from external environmental factors such as water turbidity and light scattering.Further-more,such methods involve complex image feature extraction and matrix operations,placing higher demands on the com-puting power and power consumption of the computational platform carried by the AUV.Addressing the issues of limited AUV computing power,poor real-time performance of traditional visual methods,and high computational load,this paper proposes a hardware-software integrated lightweight high-speed optical positioning scheme.This study constructs an AUV guidance model based on a multi-quadrant photoelectric detector.In terms of hardware,this scheme uses an 8×8 array multi-quadrant area detector mounted on the front of the AUV as the signal receiver,with a group of three light-emitting di-ode(LED)guidance lights arranged in an equilateral triangle deployed at the front of the recovery station as the signal trans-mitter.The detector calculates the incident deviation angles of the three optical signals by measuring the centroid position of the incident light spots,avoiding the massive image matrix calculations of traditional visual systems.In the mathematical model,this paper establishes the mapping relationship from angular deviation information to relative spatial coordinates.Considering that the AUV's roll angle is constrained during the structural design phase,information regarding the roll angle is removed from this model,effectively reducing positioning accuracy degradation caused by attitude measurement errors and enhancing system robustness.Addressing the non-linear solving problem in space,this paper introduces an improved particle swarm optimization(PSO)algorithm,using the sum of errors between the predicted deviation angles and the actual measured deviation angles as the loss function,achieving rapid estimation of the AUV's relative pose.To verify the perfor-mance of this algorithm,this paper conducted physical simulations and sea trial validations.First,based on a physical mod-el,a simulation dataset containing 100 000 sets of different data was generated,covering different distance and attitude in-formation within 0 m to 20 m.Subsequently,the algorithm was deployed on the low-power edge computing platform Jetson Orin NX for actual testing.Experimental results show that in terms of speed,the system can stably solve for the AUV's pose information at a frequency of 192 Hz;in terms of accuracy,within the terminal guidance distance of 0.6 m to 2 m,the average positioning error of this algorithm is only 7.81 mm;within the medium-to-long guidance distance of 2 m to 20 m,the average positioning error is 159.90 mm.Furthermore,in sea trial experiments based on a remotely operated vehicle(ROV),this paper used global positioning system(GPS)data as the ground truth benchmark.After deducting hardware baseline er-rors,the accuracy level of the simulation experiments was maintained,further illustrating the robustness and efficiency of the algorithm in a real underwater environment.Compared with existing vision-based guidance methods,this method dem-onstrates specific advantages in computational load and power consumption while ensuring millimeter-level guidance posi-tioning accuracy:the floating-point operations for a single solution of this algorithm are reduced to 1 million floating-point operations per second(MFLOPs),a decrease of 2 to 3 orders of magnitude compared to other methods listed in the paper,and the operating power consumption on the Jetson Orin NX is only about 10 W.This research further alleviates the contra-diction between the requirements for high accuracy,high speed,and low computing power in the underwater terminal guid-ance of AUVs,providing a new approach for the efficient autonomous docking of edge-type underwater robots.关键词
光学导引/AUV水下回收/多象限光电探测/粒子群算法/轻量化/边缘计算Key words
optical guidance/AUV docking/multi-quardant photoelectric detection/particle swarm optimization al-gorithm/lightweight/edge computing分类
信息技术与安全科学引用本文复制引用
谢正斌,孙哲,战绪丰,李学龙..高精度高速度低算力的AUV水下导引光学定位方法[J].电子学报,2026,54(1):141-152,12.基金项目
国家重点研发计划(No.2022YFC2808003) （No.2022YFC2808003）
陕西省自然科学基础研究计划面上项目(No.2024JC-YBMS-468) National Key Research and Development Program of China(No.2022YFC2808003) （No.2024JC-YBMS-468）
Natural Science Basic Research Program of Shaanxi(No.2024JC-YBMS-468) （No.2024JC-YBMS-468）
