An Experiment on Stranding Avoidance System Using Radar Image Matching

Hayashi, Shogo; Kuwashima, Susumu; Sotooka, Koukichi; Yamazaki, Hisao; Murase, Hiroshi

doi:10.9749/jin.83.257

Cited by 3 publications

(5 citation statements)

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“…Thus, they are not suitable for use in route planning that considers multiple goals. Hayashi and Kuwajima (1991) employ a fully automatic stranding avoidance system that uses radar matching to obtain positions with high precision, and to make judgments concerning the danger of stranding. Harris et al (1999) used a neuro-fuzzy network multiple ahead predictor model on ship steering dynamics, with rudder deflection angle as system input and ship directional angle as system output using a waypoint guidance scheme based on line-of-sight.…”

Section: Previous Workmentioning

confidence: 99%

“…Hayashi and Kuwajima (1991) employ a fully automatic stranding avoidance system that uses radar matching to obtain positions with high precision, and to make judgments concerning the danger of stranding. Here, a lot of the research uses the geometric approach to resolve the collision avoidance problem, seeking the shortest obstacle avoidance route.…”

Section: Introductionmentioning

confidence: 99%

“…It has been suggested that 85 percent of all marine collisions and groundings are due to human error (Dove, et al, 1986). In marine grounding cases, 22 percent of the cases are due to inadequate route planning (Hayashi & Kuwajima, 1991). In particular, an optimal route plan has a huge impact on ship navigation; if a route that avoids danger zones can be thoroughly planned prior to sailing, the number of navigational accidents can be lowered and navigational safety thus improved.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Integration of a Geographic Information System and Evolutionary Computation for Automatic Routing in Coastal Navigation

Tsou¹

2010

J. Navigation

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Suitable route planning is related to the safety and economy of navigation. However, route planning has become increasingly complex over the years and the planning process requires a large amount of oceanic environmental information. In order to use the oceanic environmental information effectively and improve the efficiency of route planning, this research employed a Geographic Information System (GIS) as the platform for enabling two-phase automatic route generation design. Firstly, through GIS's spatial data management, spatial analysis and geometric computation capability, the presence of the obstacle is detected and candidate routes are automatically generated. These are provided to the evolutionary algorithm as the basis for preliminary population calculation. Then, a specially designed evolutionary algorithm is used for route elimination to obtain the optimal route, resulting in the most-recommended routes that encompass safety and economy. This technique is more efficient than evolutionary computation techniques that use traditional random searches. At the same time, this targets safety and economy, providing a reference for developing a route planning strategy. K E Y

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Section: Previous Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integration of a Geographic Information System and Evolutionary Computation for Automatic Routing in Coastal Navigation

Tsou¹

2010

J. Navigation

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“…The system was developed for guiding ships in oceanic an coastal navigational conditions in a fully automated manner, without crew interference, only being in touch with land-based services. A collision avoiding system restricted waters was developed by Hayashi et al [4]. That system made use of an electronic map and the radar operation for evaluating the actual position and giving an assessment of the overall navigational situation.…”

Section: Previous Workmentioning

confidence: 99%

Path Planning in Dynamic Environments

Śmierzchalski

Michalewicz

2005

Innovations in Robot Mobility and Control

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Abstract. The motion planning problem for mobile robots is typically formulated as follows: given a robot and a description of an environment, plan a path of the robot between two specified locations, which is collision-free and satisfies certain optimization criteria. Traditionally there are two approaches to the problem: Off-line planning, which assumes perfectly known and stable environment, and on-line planning, which focuses on dealing with uncertainties when the robot traverses the environment. On-line planning is also referred to by many researchers as the navigation problem. Additional difficulties in approaching navigation problem is that some environments are dynamic, i.e., the obstacles which are present there, need not be static. In this paper we consider a particular instance of a navigation problem, namely, a problem of computing a near-optimum trajectory of a ship. By taking into account certain boundaries of the maneuvering region, along with navigation obstacles and other moving ships, the problem of avoiding collisions at sea was reduced to a dynamic optimization task with static and dynamic constrains. The paper presents a modified version of the Evolutionary Planner/Navigator algorithm, ϑEP/N++, to address the problem. The introduction of a time parameter, the variable speed of the ship, and time-varying constraints representing movable ships, are the main features of the new system. Sample results, having the form of ship trajectories obtained using the program for navigation situations are also presented.

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Section: Previous Workmentioning

confidence: 99%

An intelligent method of ship's trajectory planning at sea

Śmierzchalski

Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383)

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In a navigation situation at sea, the decision support system should help the operator to choose a proper manoeuvre in given circumstances, teach him good habits, and enhance his general intuition on how to behave in similar situations in future. An accepted approach in those cases is a multiple criterion decision problem. In the paper a modified version of the Evolutionary Planner /Navigator algorithm, has been used as a major component of such a decision support system for computing the near optimum trajectory of a ship in given environment. By taking into account certain boundaries of the manoeuvring region, along with navigation obstacles and other moving ships, the problem of avoiding collisions at sea was reduced to a dynamic optimisation task with static and dynamic constrains. The introduction of a time parameter and moving constrains representing the passing ships is the main distinction of the new system. Sample results, having the form of ship trajectories obtained using the program for typical navigation situations are given.

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An Experiment on Stranding Avoidance System Using Radar Image Matching

Abstract: The experimented stranding avoidance system was deve 工 oped to achieve a full − automated equip −

Cited by 3 publications

References 0 publications

Integration of a Geographic Information System and Evolutionary Computation for Automatic Routing in Coastal Navigation

Integration of a Geographic Information System and Evolutionary Computation for Automatic Routing in Coastal Navigation

Path Planning in Dynamic Environments

An intelligent method of ship's trajectory planning at sea

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