In collaborative operations of multiple autonomous underwater vehicles (AUVs), the complexity of underwater environments and limited onboard energy make environmental adaptation and energy efficiency critical metrics for evaluating path quality.
Chenxin Yin, Kai Shi, Hailong Wang
doaj +1 more source
Five-Tiered Route Planner for Multi-AUV Accessing Fixed Nodes in Uncertain Ocean Environments
This article introduces a five-tiered route planner for accessing multiple nodes with multiple autonomous underwater vehicles (AUVs) that enables efficient task completion in stochastic ocean environments.
Dong, Shanling +4 more
core
This article addresses the containment control issue for multi-AUV systems with the intervention of both external disturbance and input saturation. Firstly, a distributed estimator is established for the sake of acquiring precise estimation information ...
Liangang Yin, Zheping Yan, Jian Xu
doaj +1 more source
The design and implementation of a multi-agent architecture to increase coordination efficiency in multi-AUV operations [PDF]
This research addresses the problem of coordinating multiple autonomous underwater vehicle (AUV) operations. An intelligent mission executive has been created that uses multi-agent technology to control and coordinate multiple AUVs in communication ...
Sotzing, Christopher Carson
core
Time-varying reliability indexes for multi-AUV cooperative system
With the development of multi-autonomous underwater vehicle (AUV) cooperative systems, the evaluation of their reliability is becoming more and more important. Since AUVs are always in motion, the reliability of the system is not stationary, but it varies with time.
openaire +1 more source
Physical Behaviours for Trust Assessment in Autonomous Underwater MANETs [PDF]
This paper proposes a new approach to determine trust in resource-constrained networks of autonomous systems based on their physical behaviour, using the motion of nodes within a team to detect and identify malicious or failing operation within their ...
bolster, A, Marshall, A
core
Multi-AUV Hunting Strategy Based on Regularized Competitor Model in Deep Reinforcement Learning
Reinforcement learning has made significant progress in single-agent applications, but it still faces various challenges in multi-agent scenarios. This study investigates the application of reinforcement learning algorithms in a competitive game scenario
Yancheng Sui +3 more
doaj +1 more source
Computational intelligence approaches to robotics, automation, and control [Volume guest editors] [PDF]
No abstract ...
Chen, Yi +5 more
core
Reinforcement Learning-Based Multi-AUV Adaptive Trajectory Planning for Under-Ice Field Estimation. [PDF]
Wang C +4 more
europepmc +1 more source
Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment. [PDF]
Li J, Zhang R, Yang Y.
europepmc +1 more source

