An autonomous underwater vehicle (AUV) must use an algorithm to plan its path to distant, mobile offshore objects. Because of the uneven distribution of obstacles in the real world, the efficiency of the algorithm dec...An autonomous underwater vehicle (AUV) must use an algorithm to plan its path to distant, mobile offshore objects. Because of the uneven distribution of obstacles in the real world, the efficiency of the algorithm decreases if the global environment is represented by regular grids with all of them at the highest resolution. The framed quadtree data structure is able to more efficiently represent the environment. When planning the path, the dynamic object is expressed instead as several static objects which are used by the path planner to update the path. By taking account of the characteristics of the framed quadtree, objects can be projected on the frame nodes to increase the precision of the path. Analysis and simulations showed the proposed planner could increase efficiency while improving the ability of the AUV to follow an object.展开更多
This paper presents the possibilities of job optimization in waterway with multiple locks and canals, in order to increase the system productivity. Safe navigation in such complex waterway system is very demanding. So...This paper presents the possibilities of job optimization in waterway with multiple locks and canals, in order to increase the system productivity. Safe navigation in such complex waterway system is very demanding. Some of the problems that need to be solved are： How to control traffic in a way that vessels move in opposite directions; How to resolve possible conflicts in case that more vessels try to acquire particular lock at the same time; How to avoid possible deadlocks; How to ensure the vessel passage in the shortest possible time？ It is necessary to apply adequate control policy to avoid deadlocks and blocks the vessels＇ moving only in the case of dangerous situation. The motion of vessels can be described as the set of discrete events and states. Herein we propose deadlock avoidance algorithm for complex waterway system with multiple key resources and we use multiple re-entrant flowlines class of Petri net （MRF^PN）. The solution represents deadlock prevention supervisor in a sense that vessels are stopped only in a case of immediate dangerous situation in dense traffic. The goal of this paper is to find optimal, conflict and deadlock free job schedule in CWS. In this sense, the authors developed the algorithm which integrates MRF^PN with a genetic algorithm. The algorithm deals with multi-constrained scheduling problem with shared resources. The final goals are minimization the total travel time of vessels through the waterway system.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No. 60875071
文摘An autonomous underwater vehicle (AUV) must use an algorithm to plan its path to distant, mobile offshore objects. Because of the uneven distribution of obstacles in the real world, the efficiency of the algorithm decreases if the global environment is represented by regular grids with all of them at the highest resolution. The framed quadtree data structure is able to more efficiently represent the environment. When planning the path, the dynamic object is expressed instead as several static objects which are used by the path planner to update the path. By taking account of the characteristics of the framed quadtree, objects can be projected on the frame nodes to increase the precision of the path. Analysis and simulations showed the proposed planner could increase efficiency while improving the ability of the AUV to follow an object.
文摘This paper presents the possibilities of job optimization in waterway with multiple locks and canals, in order to increase the system productivity. Safe navigation in such complex waterway system is very demanding. Some of the problems that need to be solved are： How to control traffic in a way that vessels move in opposite directions; How to resolve possible conflicts in case that more vessels try to acquire particular lock at the same time; How to avoid possible deadlocks; How to ensure the vessel passage in the shortest possible time？ It is necessary to apply adequate control policy to avoid deadlocks and blocks the vessels＇ moving only in the case of dangerous situation. The motion of vessels can be described as the set of discrete events and states. Herein we propose deadlock avoidance algorithm for complex waterway system with multiple key resources and we use multiple re-entrant flowlines class of Petri net （MRF^PN）. The solution represents deadlock prevention supervisor in a sense that vessels are stopped only in a case of immediate dangerous situation in dense traffic. The goal of this paper is to find optimal, conflict and deadlock free job schedule in CWS. In this sense, the authors developed the algorithm which integrates MRF^PN with a genetic algorithm. The algorithm deals with multi-constrained scheduling problem with shared resources. The final goals are minimization the total travel time of vessels through the waterway system.
