Background Automatic guided vehicles(AGVs)have developed rapidly in recent years and have been used in several fields,including intelligent transportation,cargo assembly,military testing,and others.A key issue in thes...Background Automatic guided vehicles(AGVs)have developed rapidly in recent years and have been used in several fields,including intelligent transportation,cargo assembly,military testing,and others.A key issue in these applications is path planning.Global path planning results based on known environmental information are used as the ideal path for AGVs combined with local path planning to achieve safe and rapid arrival at the destination.Using the global planning method,the ideal path should meet the requirements of as few turns as possible,a short planning time,and continuous path curvature.Methods We propose a global path-planning method based on an improved A^(*)algorithm.The robustness of the algorithm was verified by simulation experiments in typical multiobstacle and indoor scenarios.To improve the efficiency of the path-finding time,we increase the heuristic information weight of the target location and avoid invalid cost calculations of the obstacle areas in the dynamic programming process.Subsequently,the optimality of the number of turns in the path is ensured based on the turning node backtracking optimization method.Because the final global path needs to satisfy the AGV kinematic constraints and curvature continuity condition,we adopt a curve smoothing scheme and select the optimal result that meets the constraints.Conclusions Simulation results show that the improved algorithm proposed in this study outperforms the traditional method and can help AGVs improve the efficiency of task execution by planning a path with low complexity and smoothness.Additionally,this scheme provides a new solution for global path planning of unmanned vehicles.展开更多
Networked rural electrification is an alternative approach to accelerate rural electrification.Using satellite photos and GIS tools,an electrical distribution network is used to connect villages and properly located g...Networked rural electrification is an alternative approach to accelerate rural electrification.Using satellite photos and GIS tools,an electrical distribution network is used to connect villages and properly located generation facilities together to reduce electrification cost.To design the network,optimal paths connecting all node-pairs are identified,followed by finding a network topology that minimizes cost.Earlier work has illustrated that A*(A-star,an optimal path-finding algorithm)is inefficient for this application due to the complex topography in rural areas.The multiplier-accelerated A*(MAA*)algorithm overcomes key performance issues,but,like A*,produces only one path connecting each node-pair.Relying on one path increases project risk because adverse conditions,such as inaccurate GIS estimation,unexpected soil conditions,land-rights disputes,political issues,etc.can occur during implementation.In this paper,a hybrid path-finding method combining genetic algorithm and A*/MAA*algorithm is proposed.The proposed method provides a family of near-optimal paths instead of a single optimal path for routing.A family of paths allows a project implementer to quickly adapt to unexpected situations as new information becomes available,and flexibly change network topology before or during implementation with minimal impact on project cost.展开更多
Wireless ad hoc network is generally employed in military and emergencies due to its flexibility and easy-to-use.It is suitable for military wireless network that has the charac-teristics of mobility and works effecti...Wireless ad hoc network is generally employed in military and emergencies due to its flexibility and easy-to-use.It is suitable for military wireless network that has the charac-teristics of mobility and works effectively under severe environment and electromagnetic interfering conditions.However,military network cannot benefit from existing routing protocol directly;there exists quite many features which are only typical for military network.For example,there are several radios in the same vehicle.This paper presents a new metric for routing,which is employed in A*algorithm.The goal of the metric is tochoose a route of less distance and less transmission delay between a source and a destination.Our metric is a function of the distance between the ends and the bandwidth over the link.Moreover,we take frequency selection into account since a node can work on multi-frequencies.This paper proposed the new metric,and experimented it based on A*algorithm.The simulation results show that this metric can find the optimal route which has less transmission delay compared to the shortest path routing.展开更多
基金Supported by the Natural Science Foundation of Jiangsu Province (BK20211037)the Science and Technology Development Fund of Wuxi (N20201011)the Nanjing University of Information Science and Technology Wuxi Campus District graduate innovation Project。
文摘Background Automatic guided vehicles(AGVs)have developed rapidly in recent years and have been used in several fields,including intelligent transportation,cargo assembly,military testing,and others.A key issue in these applications is path planning.Global path planning results based on known environmental information are used as the ideal path for AGVs combined with local path planning to achieve safe and rapid arrival at the destination.Using the global planning method,the ideal path should meet the requirements of as few turns as possible,a short planning time,and continuous path curvature.Methods We propose a global path-planning method based on an improved A^(*)algorithm.The robustness of the algorithm was verified by simulation experiments in typical multiobstacle and indoor scenarios.To improve the efficiency of the path-finding time,we increase the heuristic information weight of the target location and avoid invalid cost calculations of the obstacle areas in the dynamic programming process.Subsequently,the optimality of the number of turns in the path is ensured based on the turning node backtracking optimization method.Because the final global path needs to satisfy the AGV kinematic constraints and curvature continuity condition,we adopt a curve smoothing scheme and select the optimal result that meets the constraints.Conclusions Simulation results show that the improved algorithm proposed in this study outperforms the traditional method and can help AGVs improve the efficiency of task execution by planning a path with low complexity and smoothness.Additionally,this scheme provides a new solution for global path planning of unmanned vehicles.
文摘Networked rural electrification is an alternative approach to accelerate rural electrification.Using satellite photos and GIS tools,an electrical distribution network is used to connect villages and properly located generation facilities together to reduce electrification cost.To design the network,optimal paths connecting all node-pairs are identified,followed by finding a network topology that minimizes cost.Earlier work has illustrated that A*(A-star,an optimal path-finding algorithm)is inefficient for this application due to the complex topography in rural areas.The multiplier-accelerated A*(MAA*)algorithm overcomes key performance issues,but,like A*,produces only one path connecting each node-pair.Relying on one path increases project risk because adverse conditions,such as inaccurate GIS estimation,unexpected soil conditions,land-rights disputes,political issues,etc.can occur during implementation.In this paper,a hybrid path-finding method combining genetic algorithm and A*/MAA*algorithm is proposed.The proposed method provides a family of near-optimal paths instead of a single optimal path for routing.A family of paths allows a project implementer to quickly adapt to unexpected situations as new information becomes available,and flexibly change network topology before or during implementation with minimal impact on project cost.
文摘Wireless ad hoc network is generally employed in military and emergencies due to its flexibility and easy-to-use.It is suitable for military wireless network that has the charac-teristics of mobility and works effectively under severe environment and electromagnetic interfering conditions.However,military network cannot benefit from existing routing protocol directly;there exists quite many features which are only typical for military network.For example,there are several radios in the same vehicle.This paper presents a new metric for routing,which is employed in A*algorithm.The goal of the metric is tochoose a route of less distance and less transmission delay between a source and a destination.Our metric is a function of the distance between the ends and the bandwidth over the link.Moreover,we take frequency selection into account since a node can work on multi-frequencies.This paper proposed the new metric,and experimented it based on A*algorithm.The simulation results show that this metric can find the optimal route which has less transmission delay compared to the shortest path routing.
