Title:Design and Simulation of Multi Unmanned Boat Cooperative Obstacle
Avoidance System Based on 5G Edge Computing
Volume: 3
Author(s): Yinhui Rao, Yuanming Chen, Xiaobin Hong*Xiaodong Lin
Affiliation:
- School of Mechanical & Automotive
Engineering, South China University of Technology, Guangzhou 510641, China
Keywords:
Collaborative obstacle avoidance, unmanned boat, 5G, edge computing, path planning, obstacle detection and tracking.
Abstract:
Background: Compared to the single unmanned boat, multi-unmanned boats have
more flexible mobility and efficient task completion capabilities, which can effectively expand the
types of tasks. However, the traditional independent path planning and obstacle avoidance methods
of unmanned boats make it difficult to meet the requirements of collaborative operation
among multiple unmanned boats due to the lack of information exchange.
Objective: According to the actual demand of multi unmanned boats' cooperative operation, a
method of multi unmanned boats cooperative obstacle avoidance based on 5G edge computing is
proposed to realize the unified planning and scheduling of multi unmanned boats.
Methods: Firstly, 5G technology and Kubeedge edge computing tools are used to build a multi
unmanned boat collaborative obstacle avoidance system based on cloud, edge and end collaboration,
and the Kubeedge edge computing platform was optimized by optimizing communication
strategies, building a highly available Kubeedge cluster, building a Harbor image center, and using
Web management interfaces further to improve the reliability and stability of the system. Secondly,
the YOLOR-Deepport multi-target recognition and tracking algorithm based on cloud,
edge and end collaborative network is used to complete the recognition and tracking tasks of obstacle
targets, and a set of EECBS path planning methods based on the Kubedge centralized control
platform is designed to plan collision-free and efficient paths for each unmanned boat in realtime.
Finally, the effectiveness of the system was verified through simulation experiments.
Results: The experimental results show that compared to the traditional autonomous planning obstacle
avoidance method for unmanned boats, the collaborative planning obstacle avoidance
method proposed in this paper can exhibit excellent performance in dense and narrow scenarios,
with a more reasonable navigation path, a range reduction of 20% - 50%, and higher safety.
Conclusion: The results show that the cooperative obstacle avoidance system based on 5G edge
computing designed in the paper is feasible, and it can effectively realize the cooperative path
planning and obstacle avoidance of multi unmanned boats.
