[1]潘无为, 姜大鹏, 庞永杰, 等. 人工势场和虚拟结构相结合的多水下机器人编队控制[J]. 兵工学报, 2017, 38(2): 326-334.
PAN Wuwei, JIANG Dapeng, PANG Yongjie, et al. A multi-AUV formation algorithm combining artificial potential field and virtual structure[J]. Acta Armamentarii, 2017, 38(2): 326-334.
[2]丁家如, 杜昌平, 赵耀, 等. 基于改进人工势场法的无人机路径规划算法[J]. 计算机应用, 2016, 36(1): 287-290.
DING Jiaru, DU Changping, ZHAO Yao, et al. Path planning algorithm for unmanned aerial vehicles based on improved artificial potential field[J]. Journal of Computer Applications, 2016, 36(1): 287-290.
[3]张殿富, 刘福. 基于人工势场法的路径规划方法研究及展望[J]. 计算机工程与科学, 2013, 35(6): 88-95.
ZHANG Dianfu, LIU Fu. Research and development trend of path planning based on artificial potential field method[J]. Computer Engineering and Science, 2013, 35(6): 88-95.
[4]叶彬强, 王一. 基于人工势场法的机器人避障算法[J]. 重庆理工大学学报(自然科学), 2012, 26(9): 82-85.
YE Binqiang, WANG Yi. Research of obstacle avoidance algorithm for robot based on artificial potential field[J]. Journal of Chongqing University of Technology (Natural Science), 2012, 26(9): 82-85.
[5]张洋洋, 瞿栋, 柯俊, 等. 基于速度障碍法和动态窗口法的无人水面艇动态避障[J]. 上海大学学报(自然科学版), 2017, 23(1): 1-16.
ZHANG Yangyang, QU Dong, KE Jun, et al. Dynamic obstacle avoidance for USV based on velocity obstacle and dynamic window method[J]. Journal of Shanghai University (Natural Sciences Edition), 2017, 23(1): 1-16.
[6]徐保来, 管贻生, 苏泽荣, 等. 改进动态窗口法的阿克曼移动机器人局部路径规划器[J]. 机电工程技术, 2016, 45(9): 21-26.
XU Baolai, GUAN Yisheng, SU Zerong, et al. A modified dynamic window approach to local path planning for the Ackermann mobile robot[J]. Mechanical & Electrical Engineering Technology, 2016, 45(9): 21-26.
[7]ERIKSEN B O H, BREIVIK M, PETTERSEN K Y, et al. A modified dynamic window algorithm for horizontal collision avoidance for AUVs[C]//IEEE Conference on Control Applications. Buenos Aires, Argentina: IEEE, 2016: 499-506.
[8]程传奇, 郝向阳, 李建胜, 等. 融合改进A*算法和动态窗口法的全局动态路径规划[J]. 西安交通大学学报, 2017, 51(11): 137-143.
CHENG Chuanqi, HAO Xiangyang, LI Jiansheng, et al. Global dynamic path planning based on fusion of improved A* algorithm and dynamic window approach[J]. Journal of Xi’an Jiaotong University, 2017, 51(11): 137-143.
[9]KIM H, KIM D, SHIN J U, et al. Angular rate-constrained path planning algorithm for unmanned surface vehicles[J]. Ocean Engineering, 2014, 84: 37-44.
[10]LIKHACHEY M, KOENIG S. A generalized framework for lifelong planning A* search[C]//15th International Conference on Automated Planning and Scheduling. Monterey, CA, USA: AAAI, 2008: 99-108.
[11]张贺, 胡越黎, 王权, 等. 基于改进D*算法的移动机器人路径规划[J]. 工业控制计算机, 2016, 29(11): 73-74.
ZHANG He, HU Yueli, WANG Quan, et al. Path planning of mobile robot based on improved D* algorithm[J]. Industrial Control Computer, 2016, 29(11): 73-74.
[12]WANG Z, XIANG X B. Improved Astar algorithm for path planning of marine robot[C]//37th Chinese Control Conference. Wuhan: IEEE, 2018: 5410-5414.
[13]WANG Z, XIANG X B, YANG J, et al. Composite Astar and B-spline algorithm for path planning of autonomous underwater vehicle[C]//7th International Conference on Underwater System Technology: Theory and Applications. Kuala Lumpur, Malaysia: IEEE, 2017.
[14]徐澎. 基于行为的多AUV队形控制技术研究[D]. 上海: 上海交通大学, 2013.
XU Peng. Behavior-based formation control of multi-AUV[D]. Shanghai: Shanghai Jiao Tong University, 2013.
[15]甘文洋, 朱大奇. 基于行为策略的AUV全覆盖信度函数路径规划算法[J]. 系统仿真学报, 2018, 30(5): 1857-1868.
GAN Wenyang, ZHU Daqi. Complete coverage belief function path planning algorithm of autonomous underwater vehicle based on behavior strategy[J]. Journal of System Simulation, 2018, 30(5): 1857-1868.
[16]魏立新, 吴绍坤, 孙浩, 等. 基于多行为的移动机器人路径规划[J]. 控制与决策, 2018, 34(12): 2721-2726.
WEI Lixin, WU Shaokun, SUN Hao, et al. Mobile robot path planning based on multi-behaviors[J]. Control and Decision, 2018, 34(12): 2721-2726.
[17]高剑, 李勇强, 徐德民, 等. 基于行为的自主水下航行器无碰路径跟踪控制[J]. 大连海事大学学报, 2012, 38(4): 30-34.
GAO Jian, LI Yongqiang, XU Demin, et al. Behavior-based collision free path following control of an autonomous underwater vehicle[J]. Journal of Dalian Maritime University, 2012, 38(4): 30-34.
[18]ROSALES C, LEICA P, SARCINELLI-FILHO M, et al. 3D formation control of autonomous vehicles based on null-space[J]. Journal of Intelligent & Robotic Systems, 2016, 84(1/2/3/4): 453-467.
[19]程玉虎, 易建强, 赵冬斌. 机器人行为协调机制研究进展[J]. 机器人, 2004, 26(2): 187-192.
CHENG Yuhu, YI Jianqiang, ZHAO Dongbin. The progress of the behavior coordination mechanism for robots[J]. Robot, 2004, 26(2): 187-192.
[20]邬林波. 基于NSB方法的多机器人编队控制[D]. 长沙: 国防科学技术大学, 2010.
WU Linbo. Multi-robots formation control based on null-space-based method[D]. Changsha: National University of Defense Technology, 2010.
[21]ANTONELLI G, ARRICHIELLO F, CHIAVERINI S. The null-space-based behavioral control for autonomous robotic systems[J]. Intelligent Service Robotics, 2008, 1(1): 27-39.
[22]DO K D, PAN J. Control of ships and underwater vehicles: Design for underactuated and nonlinear marine systems[M]. UK: Springer Science & Business Media, 2009. |