A two-step control approach for docking of autonomous underwater vehicles

2014 ◽  
Vol 25 (10) ◽  
pp. 1528-1547 ◽  
Author(s):  
Pedro Batista ◽  
Carlos Silvestre ◽  
Paulo Oliveira
2021 ◽  
Vol 9 (4) ◽  
pp. 355
Author(s):  
Tao Chen ◽  
Xingru Qu ◽  
Zhao Zhang ◽  
Xiao Liang

In this article, a distributed cooperative path-maneuvering control approach is developed for the region-searching of multiple autonomous underwater vehicles under both dynamic uncertainties and ocean currents. Salient contributions are as follows: (1) by virtue of boustrophedon motions and trigonometric functions, the coverage path-planning design is first proposed to generate multiple parameterized paths, which can guarantee that the region-searching is successfully completed by one trial; (2) combining with sliding mode and adaptive technique, distributed maneuvering control laws for surge and yaw motions are employed to drive vehicles to track the assigned paths, thereby contributing to the cooperative maneuvering performance with high accuracy; (3) by the aid of graph theory, the distributed signal observer-based consensus protocols are developed for path parameter synchronization, and successfully apply to maintain the desired formation configuration. The globally asymptotical stability of the closed-loop signals is analyzed via the direct Lyapunov approach, and simulation studies on WL-II are conducted to illustrate the remarkable performance of the proposed path-maneuvering control approach.


Author(s):  
Thomas Glotzbach ◽  
Ju¨rgen Wernstedt

In this paper we discuss the further development of approaches for the control of vehicles with Adaptive Autonomy that have already been successfully used in single Autonomous Underwater Vehicles (AUVs) for cooperating teams of AUVs. A hierarchical control approach for a single AUV based on the Rational Behaviour Model (RBM) is presented. After the explanation of the concept of Adaptive Autonomy, this concept will be used to transfer the RBM- approach for single AUVs into another which can be used for the control of teams of AUVs. This new concept will contain a software task called ‘team instance’ that is responsible for the realisation of the cooperation between the vehicles. Finally, two concepts for the realisation of the ‘team instance’ are discussed and compared with each other, referring to possible real missions with teams of AUVs.


2021 ◽  
Vol 9 (2) ◽  
pp. 162
Author(s):  
Cris Thomas ◽  
Enrico Simetti ◽  
Giuseppe Casalino

This research proposes a unified guidance and control framework for Autonomous Underwater Vehicles (AUVs) based on the task priority control approach, incorporating various behaviors such as path following, terrain following, obstacle avoidance, as well as homing and docking to stationary and moving stations. The integration of homing and docking maneuvers into the task priority framework is thus a novel contribution of this paper. This integration allows, for example, to execute homing maneuvers close to uneven seafloor or obstacles, ensuring the safety of the AUV, as safety tasks can be given the highest priority. Furthermore, another contribution shown in the paper is that the proposed approach tackles a wide range of scenarios without ad hoc solutions. Indeed, the proposed approach is well suited for both the emerging trend of resident AUVs, which stay underwater for a long period inside garage stations, exiting to perform inspection and maintenance missions and homing back to them, and for AUVs that are required to dock to moving stations such as surface vehicles, or towed docking stations. The proposed techniques are studied in a simulation setting, taking into account the rich number of aforementioned scenarios.


2019 ◽  
Vol 16 (4) ◽  
pp. 172988141987066 ◽  
Author(s):  
Xiang Cao ◽  
Liqiang Guo

As one of the challenging tasks of multiple autonomous underwater vehicles systems, the realization of target hunting is the great significance. The multiple autonomous underwater vehicle target hunting is studied in this article. In some research, because the hunting members cannot reach the hunting point at the same time, the hunting time is long or the target escapes. To improve the efficiency of the target hunting, the leader–follower formation algorithm is introduced. Firstly, the task is assigned based on the distance between the autonomous underwater vehicle and the target. Then, the autonomous underwater vehicles with the same task are formed based on leader–follower mode, and the formation is kept to track the target. In the final capture phase, multiple autonomous underwater vehicle system use angle matching algorithm to round up target. The simulation results show that the proposed algorithm can effectively accomplish the target hunting task, save the hunting time, and avoid the target escape. Compared with the bioinspired neural network algorithm, the proposed algorithm shows better performance.


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