Path Planning for Autonomous Ships: A Hybrid Approach Based on Improved APF and Modified VO Methods

Collision Avoidance Decision Method for Unmanned Surface Vehicle Based on an Improved Velocity Obstacle Algorithm

To ensure navigation safety, unmanned surface vehicles (USVs) need to have autonomous collision avoidance capability. A large number of studies on ship collision avoidance are available, and most of these papers assume that the target ships keep straight or follows the International Regulations for Preventing Collisions at Sea (COLREGS). However, in the actual navigation process, the target ship may temporarily turn. Based on the above reasons, this paper proposes a multi-ship collision avoidance decision method for USVs based on the improved velocity obstacle algorithm. In the basic dynamic ship domain model, a collision risk model is constructed to improve the accuracy of the risk assessment between the USV and target ships. The velocity obstacle algorithm is combined with the dynamic ship domain, and the collision avoidance timing and method are judged according to the collision risk. The simulation results show that the decision method can handle the situation that the target ship temporarily turns and has an emergency collision avoidance capability. Compared with the traditional VO algorithm, the collision avoidance time of the method is shorter, and the number of course changes is less.

Marine Adaptive Sampling Scheme Design for Mobile Platforms under Different Scenarios

Marine adaptive sampling is a technique that makes full use of limited observation resources by selecting the optimal positions. Recently, the design of an adaptive sampling scheme based on a mobile platform has become a research hotspot. However, adaptive sampling system involves multiple subsystems, and the attributes as well as tasks are always different, which may lead to different sampling scenarios. A great deal of research has been conducted for specific situations, especially with fixed starting and ending points. However, systematic design and simulation experiments under various circumstances are still lacking. How to design the adaptive observation system, so as to cope with the observation task under different scenarios, is still a problem worth studying. Aiming to solve this problem, we designed a systematic scheme design process. The process includes setting up and verifying the background field, adopting the hierarchical optimization framework to adapt to different circumstances, and variable adjustments for twin frames. The needs covered in this paper include not having a fixed starting point and ending point, only having a fixed starting point, having a fixed starting point and ending point, increasing sampling coverage, and simple obstacle avoidance. Finally, the relevant conclusions are applied to the multi-platform simultaneous observation scenario. It provides a systematic flow pattern for designing adaptive sampling scheme of mobile platforms.