Global path planning problem for autonomous underwater vehicle (AUV) based on large-scale chart data is investigated by using ant colony optimization (in shorts, ACO) algorithm.
在大范围海洋环境中，应用蚁群算法对自主式水下潜器(AUV)的全局路径规划问题进行了研究。
To solve the problem of path planning of LAUV (Long-distance Autonomous Underwater Vehicle), a path planning algorithm based on digital charts is presented.
为了解决远程自主水下机器人(LAUV)路径规划问题，提出一种基于数字海图的路径规划算法。
Frist, the constitution of AUV system is presented. Next, path planning method of AUV is discussed. Global and local path planner that shows the autonomous ability is especially introduced.
首先介绍了自行研制的智能水下机器人的系统组成，然后讨论了其规划方法，并着重介绍了体现水下智能机器人自主能力的全局规划器和局部规划器。
Aiming at the problem of real-time obstacle avoidance for autonomous virtual humans in dynamic unknown environment, this paper presents a path planning model based on the mixed perception information.
针对动态未知环境下的自主虚拟人实时避障问题，提出一种基于混合感知信息的路径规划模型。
The path search using Steepest Descent Approach, the cross country path planning about fuzzy environment for an autonomous land vehicle is implemented.
最后用最速下降法进行路径搜索，实现了自主车在模糊环境下的越野路径规划。
Path planning is an important link of underwater vehicle carrying out autonomous voyage, which marks the working level and ensures the safety of AUV.
路径规划是水下机器人实现自主航行的重要环节。
This paper presents the design and implementation of cross-country path planning for an autonomous land vehicle based on a heuristic search method.
本文介绍了一种使用启发式估值函数进行二次搜索的路径规划方法，设计和实现了自主车的越野路径规划。
This paper presents the design and implementation of cross-country path planning for an autonomous land vehicle based on a heuristic search method.
本文介绍了一种使用启发式估值函数进行二次搜索的路径规划方法，设计和实现了自主车的越野路径规划。
应用推荐