[1] [1] 1孙兆伟， 刘雪奎， 吴限德， 等. 用于通信保障航天器的遗传蚁群融合路径规划［J］. 光学 精密工程， 2013， 21（12）： 3308-3316. doi: 10.3788/ope.20132112.3308SUNZH W， LIUX K， WUX D， et al. Path planning based on ant colony and genetic fusion algorithm for communication supporting spacecraft［J］. Opt. Precision Eng.， 2013， 21（12）： 3308-3316.（in Chinese）. doi: 10.3788/ope.20132112.3308

[2] [2] 2颜雪松， 胡成玉， 姚宏， 等. 精英粒子群优化算法及其在机器人路径规划中的应用［J］. 光学 精密工程， 2013， 21（12）： 3160-3168. doi: 10.3788/ope.20132112.3160YANX S， HUCH Y， YAOH， et al. Elite particle swarm optimization algorithm and its application in robot path planning［J］. Opt. Precision Eng.， 2013， 21（12）： 3160-3168.（in Chinese）. doi: 10.3788/ope.20132112.3160

[3] [3] 3赵海， 陈星池， 王家亮， 等. 基于四轴飞行器的单目视觉避障算法［J］. 光学 精密工程， 2014， 22（8）： 2232-2241. doi: 10.3788/ope.20142208.2232ZHAOH， CHENX CH， WANGJ L， et al. Obstacle avoidance algorithm based on monocular vision for quad-rotor helicopter［J］. Opt. Precision Eng.， 2014， 22（8）： 2232-2241.（in Chinese）. doi: 10.3788/ope.20142208.2232

[4] L HU, W NAEEM, E RAJABALLY et al. A multiobjective optimization approach for COLREGs-compliant path planning of autonomous surface vehicles verified on networked bridge simulators. IEEE Transactions on Intelligent Transportation Systems, 21, 1167-1179(2020).

[5] J PARK, J CHOI, H T CHOI. COLREGS-compliant path planning considering time-varying trajectory uncertainty of autonomous surface vehicle. Electronics Letters, 55, 222-224(2019).

[6] T A JOHANSEN, T PEREZ, A CRISTOFARO. Ship collision avoidance and COLREGS compliance using simulation-based control behavior selection with predictive hazard assessment. IEEE Transactions on Intelligent Transportation Systems, 17, 3407-3422(2016).

[7] Z CHEN, Y M ZHANG, Y G ZHANG et al. A hybrid path planning algorithm for unmanned surface vehicles in complex environment with dynamic obstacles. IEEE Access, 7, 126439-126449(2019).

[8] X G LIN, R X GUO. Path planning of unmanned surface vehicle based on improved Q-learning algorithm, 302-306(2019).

[9] W C ZHANG, Y M XU, J P XIE. Path planning of USV based on improved hybrid genetic algorithm, 1-7(2019).

[10] N KIM. Collision avoidance for an unmanned surface vehicle using deep reinforcement learning. Ocean Engineering, 199, 107001(2020).

[11] [11] 11洪晓斌， 魏新勇， 黄烨笙， 等. 融合图像识别和VFH+的无人艇局部路径规划方法［J］. 华南理工大学学报：自然科学版， 2019， 47（10）： 24-33. doi: 10.1109/ccdc49329.2020.9163979HONGX B， WEIX Y， HUANGY SH， et al. Local path planning method for unmanned surface vehicle based on image recognition and VFH+［J］. Journal of South China University of Technology： Natural Science Edition， 2019， 47（10）： 24-33.（in Chinese）. doi: 10.1109/ccdc49329.2020.9163979

[12] [12] 12尚明栋， 朱志宇， 周涛. 水面无人艇动态避碰策略研究［J］. 舰船科学技术， 2017， 39（17）： 69-73. doi: 10.3404/j.issn.1672-7649.2017.09.014SHANGM D， ZHUZH Y， ZHOUT. Research on dynamic intelligent anti-collision of USV［J］. Ship Science and Technology， 2017， 39（17）： 69-73.（in Chinese）. doi: 10.3404/j.issn.1672-7649.2017.09.014