scholarly journals Unified Dynamics-based Motion Planning Algorithm for Autonomous Underwater Vehicle-Manipulator Systems (UVMS)

10.5772/4779 ◽  
2007 ◽  
Author(s):  
Tarun K. ◽  
Nilanjan Sarkar
Keyword(s):  
Motion Planning ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Planning Algorithm

scholarly journals A unified dynamics-based motion planning algorithm for autonomous underwater vehicle-manipulator systems (UVMS)

Robotica ◽  
2004 ◽  
Vol 22 (1) ◽  
pp. 117-128 ◽  
Author(s):  
Tarun Kanti Podder ◽  
Nilanjan Sarkar
Keyword(s):  
Motion Planning ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Dynamic Responses ◽  
Hydrodynamic Drag ◽  
Actuator Faults ◽  
Kinematic Redundancy ◽  
Planning Algorithm ◽  
Dynamic Bandwidth ◽  
Reference Trajectories

A new unified motion planning algorithm for autonomous Underwater Vehicle-Manipulator Systems (UVMS) has been presented in this paper. Commonly, a UVMS consists of two sub-systems, a vehicle and a manipulator, having vastly different dynamic responses. The proposed algorithm considers the variability in dynamic bandwidth of the complex UVMS system and generates not only kinematically admissible but also dynamically feasible reference trajectories. Additionally, this motion planning algorithm exploits the inherent kinematic redundancy of the whole system and provides reference trajectories that accommodates other important criteria such as thruster/actuator faults and saturations, and also minimizes hydrodynamic drag. Effectiveness of the proposed unified motion planning algorithm has been verified by extensive computer simulation. The results are quite promising.

Autonomous Underwater Vehicle Motion Planning via Sampling Based Model Predictive Control

2014 ◽  
Vol 670-671 ◽  
pp. 1370-1377 ◽  
Author(s):  
Lin Lin Wang ◽  
Hong Jian Wang ◽  
Li Xin Pan
Keyword(s):  
Model Predictive Control ◽  
Motion Planning ◽  
Predictive Control ◽  
Autonomous Underwater Vehicle ◽  
Angular Rate ◽  
Control Variable ◽  
Underwater Vehicle ◽  
Planning Optimization ◽  
Sampling Points ◽  
Rolling Optimization

In order to improve the ability of independent planning for AUV (Autonomous Underwater Vehicle), a new method of motion planning based on SBMPC (Sampling Based Model Predictive Control) is proposed, which is combined with model predictive control theory. Input sampling is directly made in control variable space, and sampling data is substituted into the predictive model of AUV motion. Then surge velocity and yaw angular rate in next sampling time are obtained through calculations. If predictive states are evaluated according to the performance index previously defined, optimal prediction of AUV states in next sampling can be used to realize motion planning optimization. Effects of three sampling methods (viz. uniform sampling, Halton sampling and CVT sampling) on motion planning performance are also compared in simulations. Statistical analysis demonstrates that CVT sampling points has the most uniform coverage in two-dimensional plane when amount of sampling points is the same for three methods. Simulation results show that it is effective and feasible to plan a route for AUV by using CVT sampling and rolling optimization of MPC (Model Predictive Control).

scholarly journals Cognition-based hybrid path planning for autonomous underwater vehicle target following

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141985755 ◽  
Author(s):  
Li Yue Ming ◽  
Huang Hai ◽  
Xu Yang ◽  
Zhang Guocheng ◽  
Li Jiyong ◽  
...  
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Target Detection ◽  
Optimization Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Cognitive Architecture ◽  
Underwater Vehicle ◽  
Fuzzy Rules ◽  
Mobile Target

Intelligent path planning is one of the key techniques for autonomous underwater vehicles for the purpose of target detection, environmental survey and so on. In order to realize automatic motion plan, an intelligent cognitive architecture for autonomous underwater vehicle motion planning has been proposed to realize complicated target detection and mobile target following in the disturbance environment. A novel adaptive ant colony optimization and particle swarm optimization fusion-based fuzzy rules optimization algorithm has been proposed to generate optimized fuzzy rules. Through this optimization algorithm, the preliminary fuzzy rules can be optimized to realize intelligent motion planning for complicated operation tasks. Experiments of channel following for wall detection and mobile target following in the oceanic environment have verified the validity of path planning method in the implementation of detection and operation tasks.

A Novel Path Planning Algorithm for Autonomous Underwater Vehicle

2013 ◽  
Vol 446-447 ◽  
pp. 1271-1278
Author(s):  
Bo Yin ◽  
Bing Liu ◽  
Jing Cao
Keyword(s):  
Path Planning ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Moving Simulation ◽  
Path Planning Algorithm

A path planning algorithm based on sector scanning for AUV was proposed in this paper. By reducing the frequency of the calculation of the path planning, this method solved the problem that AUV can not respond to the frequent control instructions of path planning because of AUV’s poor flexibility. Meanwhile, by making the path more clear and reliable, the algorithm improved the operability of responding to the path planning results and operating the controlling of AUV’s moving. Simulation results show that this method is feasible and efficient.

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