Abstract
Unmanned surface vehicles (USVs) are new marine intelligent platforms that can autonomously operate in various ocean environments with intelligent decision-making capability. As one of key technologies enabling such a capability, path planning algorithms underpin the navigation and motion control of USVs by providing optimized navigational trajectories. To accommodate complex maritime environments that include various static/moving obstacles, it is important to develop a computational efficient path planning algorithm for USVs so that real-time operation can be effectively carried out. This paper therefore proposes a new algorithm based on the fast sweeping method, named the locking sweeping method (LSM). Compared with other conventional path planning algorithms, the proposed LSM has an improved computational efficiency and can be well applied in dynamic environments that have multiple moving obstacles. When generating an optimal collision-free path, moving obstacles are modelled with ship domains that are calculated based upon ships’ velocities. To evaluate the effectiveness of the algorithm, particularly the capacity in dealing with practical environments, three different sets of simulations were undertaken in environments built using electronic nautical charts (ENCs). Results show that the proposed algorithm can effectively cope with complex maritime traffic scenarios by generating smooth and safe trajectories.
Highlights
In recent years, the exploration and exploitation of the ocean have received increasing attention
Simulations are first conducted to compare the fast marching method (FMM), fast sweeping method (FSM), and locking sweeping method (LSM) algorithms to show the computing efficiency provided by the LSM with the comparisons carried out in free spaces, areas with simple obstacles, and practical maritime environments
The second set of tests are carried out using electronic nautical charts (ENCs) information from Dalian sea area with the results showing that trajectories can always be well generated to avoid both complex static and dynamic obstacles
Summary
The exploration and exploitation of the ocean have received increasing attention. The core modules of USVs include sensor, communication, motion control, and decision processing modules These modules work collaboratively to achieve autonomous navigation for USVs (autonomy refers to the ability to interact with the external environment). One of the most important aspects of USVs is their ability to select a safe and effective motion mode according to information describing the surrounding environment. Such a capability is referred to as path planning technology, which is a key autonomous decision-making functionality and forms the basis of the navigation and motion control of a USV
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