多元智能理论（the Theory of Multiple Intelligences）简称MI理论,是由美国哈佛大学心理学家Howard Gardner在1985提出的。他认为,人的智能是多元的,在个体身上相对独立存在、与特定的认知领域或知识范畴相联系的有八种智能。多元智...多元智能理论（the Theory of Multiple Intelligences）简称MI理论,是由美国哈佛大学心理学家Howard Gardner在1985提出的。他认为,人的智能是多元的,在个体身上相对独立存在、与特定的认知领域或知识范畴相联系的有八种智能。多元智能理论给我国的教育教学实践带来了许多启示,大学英语教学在这一理论的指导下能够使自己的教学模式走向多层次、多样化。展开更多
With the rapid development of Unmanned Aerial Vehicle(UAV)technology,one of the emerging fields is to utilize multi-UAV as a team under autonomous control in a complex environment.Among the challenges in fully achievi...With the rapid development of Unmanned Aerial Vehicle(UAV)technology,one of the emerging fields is to utilize multi-UAV as a team under autonomous control in a complex environment.Among the challenges in fully achieving autonomous control,Cooperative task assignment stands out as the key function.In this paper,we analyze the importance and difficulties of multiUAV cooperative task assignment in characterizing scenarios and obtaining high-quality solutions.Furthermore,we present three promising directions for future research:Cooperative task assignment in a dynamic complex environment,in an unmanned-manned aircraft system and in a UAV swarm.Our goal is to provide a brief review of multi-UAV cooperative task assignment for readers to further explore.展开更多
The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments.The underwater environment is still considered as a great ...The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments.The underwater environment is still considered as a great challenge for the path planning of autonomous underwater vehicles(AUVs)because of its hostile and dynamic nature.The major constraints for path planning are limited data transmission capability,power and sensing technology available for underwater operations.The sea environment is subjected to a large set of challenging factors classified as atmospheric,coastal and gravitational.Based on whether the impact of these factors can be approximated or not,the underwater environment can be characterized as predictable and unpredictable respectively.The classical path planning algorithms based on artificial intelligence assume that environmental conditions are known apriori to the path planner.But the current path planning algorithms involve continual interaction with the environment considering the environment as dynamic and its effect cannot be predicted.Path planning is necessary for many applications involving AUVs.These are based upon planning safety routes with minimum energy cost and computation overheads.This review is intended to summarize various path planning strategies for AUVs on the basis of characterization of underwater environments as predictable and unpredictable.The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.展开更多
文摘多元智能理论（the Theory of Multiple Intelligences）简称MI理论,是由美国哈佛大学心理学家Howard Gardner在1985提出的。他认为,人的智能是多元的,在个体身上相对独立存在、与特定的认知领域或知识范畴相联系的有八种智能。多元智能理论给我国的教育教学实践带来了许多启示,大学英语教学在这一理论的指导下能够使自己的教学模式走向多层次、多样化。
基金supported in part by the National Natural Science Foundation of China(Nos.61671031,61722102,91738301)。
文摘With the rapid development of Unmanned Aerial Vehicle(UAV)technology,one of the emerging fields is to utilize multi-UAV as a team under autonomous control in a complex environment.Among the challenges in fully achieving autonomous control,Cooperative task assignment stands out as the key function.In this paper,we analyze the importance and difficulties of multiUAV cooperative task assignment in characterizing scenarios and obtaining high-quality solutions.Furthermore,we present three promising directions for future research:Cooperative task assignment in a dynamic complex environment,in an unmanned-manned aircraft system and in a UAV swarm.Our goal is to provide a brief review of multi-UAV cooperative task assignment for readers to further explore.
文摘The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments.The underwater environment is still considered as a great challenge for the path planning of autonomous underwater vehicles(AUVs)because of its hostile and dynamic nature.The major constraints for path planning are limited data transmission capability,power and sensing technology available for underwater operations.The sea environment is subjected to a large set of challenging factors classified as atmospheric,coastal and gravitational.Based on whether the impact of these factors can be approximated or not,the underwater environment can be characterized as predictable and unpredictable respectively.The classical path planning algorithms based on artificial intelligence assume that environmental conditions are known apriori to the path planner.But the current path planning algorithms involve continual interaction with the environment considering the environment as dynamic and its effect cannot be predicted.Path planning is necessary for many applications involving AUVs.These are based upon planning safety routes with minimum energy cost and computation overheads.This review is intended to summarize various path planning strategies for AUVs on the basis of characterization of underwater environments as predictable and unpredictable.The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.
