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Download Trajectory Planning for Autonomous Underwater Vehicles: A Fast Marching based method for global trajectory planning djvu

by Clement Petres

Author: Clement Petres
Subcategory: Engineering
Language: English
Publisher: LAP LAMBERT Academic Publishing (October 5, 2010)
Pages: 180 pages
Category: Engineering and Transport
Rating: 4.6
Other formats: lit mbr txt rtf

The Fast Marching method, as one of these trajectory planning . The main contribution of the authors is to present a Fast Marching based method as an. advanced tool for underwater trajectory planning (Petres et a. 2007).

This led us to develop a new algorithm, called FM, that combines the exploration efficiency of the A algorithm with the accuracy of the Fast Marching method. For these reasons, the FM algorithm opens new possibilities for planning trajectories in wide and continuous underwater environments.

methods based on local perceptions are computationally less. for autonomous underwater vehicles based on BK-products of. expensive and thus time ecient. constraints by simulating vehicle trajectory using advanced. simulator, modeling the perception abilities of the forward. looking sonar, and the obstacles detection in realtime. fuzzy relation, Fuzzy Sets and Systems,vol. ] V. Kanakakis, K. P. Valavanis, and N. C. Tsourveloudis, Fuzzy-. logic based navigation of underwater vehicles, Journal of.

1 Trajectory planning This chapter is a contribution to the field of Artificial Intelligence. oceedings{PF, title {Trajectory planning for autonomous underwater vehicles}, author {Clement Petres}, year {2007} }. Clement Petres. Artificial Intelligence can be defined as the study of methods by which a computer can simulate aspects of human intelligence (Moravec, 2003). Among many mental capabilities, a human being is able to find his own path in a given environment and to optimize it according to the situation requirements.

The overall Fast Marching based trajectory planning method has been tested on simulated underwater environments and validated on a real . A Fast Marching based method for global trajectory planning.

The overall Fast Marching based trajectory planning method has been tested on simulated underwater environments and validated on a real experimental platform in open water. LAP Lambert Academic Publishing ( 2010-10-05 ).

Trajectory Planning for Autonomous Underwater Vehicles. Over 21,000 IntechOpen readers like this topic. Help us write another book on this subject and reach those readers. By Clement Petres, Yan Pailhas, Pedro Patron, Jonathan Evans, Yvan Petillot and Dave Lane. Published: January 1st 2009. 2131total chapter downloads.

Path planning and obstacle avoidance are an important issues for Autonomous Underwater Vehicles (AUVs) . Planning methods based on local perceptions are computationally less expensive and thus time efficient.

Path planning and obstacle avoidance are an important issues for Autonomous Underwater Vehicles (AUVs), and as can be noticed lately, these fields are extensively studied. Currents disturbances can have a big influence in a different water depth and should be considered in underwater environments. For the first time, Soulignac et al. faced with strong current situations. Bui and Kim and Kanakakis et al. apply fuzzy logic approaches to AUV path planning.

Path Planning Configuration Space Autonomous Underwater Vehicle Cell Decomposition Visibility Graph. Paull L, Saeedi S, Li H, Myers V (2010) An information gain based adaptive path planning method for an autonomous underwater vehicle using sidescan sonar. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves. In: IEEE conference on automation science and engineering (CASE), pp 835–840, 2010Google Scholar. 31. Lumelsky V, Stepanov A (1987) Path planning strategies for point mobile automaton moving amidst unknown obstacles of arbitrary shape.

The parking trajectory planning oriented optimal control problem consists of a cost function, vehicle kinematics, boundary conditions and the within-tunnel constraints.

The parking trajectory planning oriented optimal control problem consists of a cost function, vehicle kinematics, boundary conditions and the within-tunnel constraints (4). wherein w1, w2 ³ 0 are weighting parameters. As a summary, the autonomous parking trajectory planning task is described as the following optimal control problem: Minimize (4), . Kinematic constraints (1), (2); Within-tunnel constraints

considering them for planning the desired and possible trajectory to be tracked the vehicle’s control systems

Trajectory Planning for Autonomous Underwater Vehicles 399. Clement Petres, Yan Pailhas, Pedro Patron, Jonathan Evans, Yvan Petillot and Dave Lane. 22. Environmental Impact Assessment and Management of 417. Sewage Outfall Discharges using AUVʼS Patrícia Ramos and Mário V. Neves. considering them for planning the desired and possible trajectory to be tracked the vehicle’s control systems. However, there are other limitations like the pressure that the submarine can stand when the depth increases and the endurance in terms of battery power. These are still open problems from standpoint of new materials.

Trajectory planning is defined as creating motion for an end-effector (. a hand) from one point to another while avoiding collisions. From: Human Motion Simulation, 2013. Ulybyshev presented a trajectory optimization method for low-thrust spacecraft that used the discretization of a spacecraft trajectory on segments and sets of pseudoimpulses for each segment. Suzuki presented a sequential goal programming approach that considered not only well-defined flight trajectory problems but also ill-defined problems. An interval optimization was proposed according to the fixed-time multiple impulse.

Efficient trajectory planning algorithms are a crucial issue for modern autonomous underwater vehicles. Classical trajectory planning algorithms in artificial intelligence are not designed to deal with wide continuous environments prone to currents. Furthermore torpedo-like underwater vehicles are strongly nonholonomic. A novel Fast Marching based approach is proposed to address the following issues. First, the FM* algorithm is proposed to extend the A* algorithm to the continuous domain. Second, underwater currents are taken into account thanks to an anisotropic extension of the original Fast Marching algorithm. Third, the vehicle turning radius is introduced as a constraint on the curvature of the optimal trajectory for both isotropic and anisotropic media. Furthermore, a dynamic version of the Fast Marching algorithm called DFM is developed to efficiently replan trajectories in dynamic unpredictable environments. The overall Fast Marching based trajectory planning method has been tested on simulated underwater environments and validated on a real experimental platform in open water.