For autonomous Unmanned Aerial Vehicles(UAVs)flying in real-world scenarios,time for path planning is always limited,which is a challenge known as the anytime problem.Anytime planners address this by finding a collisi...For autonomous Unmanned Aerial Vehicles(UAVs)flying in real-world scenarios,time for path planning is always limited,which is a challenge known as the anytime problem.Anytime planners address this by finding a collision-free path quickly and then improving it until time runs out,making UAVs more adaptable to different mission scenarios.However,current anytime algorithms based on A^(*)have insufficient control over the suboptimality bounds of paths and tend to lose their anytime properties in environments with large concave obstacles.This paper proposes a novel anytime path planning algorithm,Anytime Radiation A^(*)(ARa A^(*)),which can generate a series of suboptimal paths with improved bounds through decreasing search step sizes and can generate the optimal path when time is sufficient.The ARa A^(*)features two main innovations:an adaptive variable-step-size mechanism and elliptic constraints based on waypoints.The former helps achieve fast path searching in various environments.The latter allows ARa A^(*)to control the suboptimality bounds of paths and further enhance search efficiency.Simulation experiments show that the ARa A^(*)outperforms Anytime Repairing A^(*)(ARA^(*))and Anytime D^(*)(AD^(*))in controlling suboptimality bounds and planning time,especially in environments with large concave obstacles.Final flight experiments demonstrate that the paths planned by ARa A^(*)can ensure the safe flight of quadrotors.展开更多
提出了一种新的Anytime分类算法,anytime averaged probabilistic under mutual information estimators(AAPMIE)。该分类算法能较好地适用于需要即时响应的在线业务。从信息论的角度认为每个属性所携带的信息量是不同的,对其他属性影...提出了一种新的Anytime分类算法,anytime averaged probabilistic under mutual information estimators(AAPMIE)。该分类算法能较好地适用于需要即时响应的在线业务。从信息论的角度认为每个属性所携带的信息量是不同的,对其他属性影响较大的属性应该具有较高的权限被优先选择作为super-parent参加分类计算,这样,有助于提高分类开始阶段的分类准确率,有助于在较少的计算资源下返回更好的分类效率。实验验证了该算法能在anytime分类的早期较好的改善分类效果降低分类的0-1损失错误率,伴随计算资源的增加,算法能进一步得到更好的分类准确率。展开更多
ZTE provides customized CDMA WLL solutions that can bring youvalue-added services under any circumstances.Flexibility:Flexible network solutions for both urban and rural areas.Expertise:Cost-effective solutions based ...ZTE provides customized CDMA WLL solutions that can bring youvalue-added services under any circumstances.Flexibility:Flexible network solutions for both urban and rural areas.Expertise:Cost-effective solutions based on CDMA2000 technology,offering wireless data services, can easily evolve to 3G.Experience:Proven technology with 90% market share in China aswell as applications in overseas countries like India and Brazil.展开更多
基金the support of the National Natural Science Foundation of China(No.52272382)the Aeronautical Science Foundation of China(No.20200017051001)the Fundamental Research Funds for the Central Universities,China。
文摘For autonomous Unmanned Aerial Vehicles(UAVs)flying in real-world scenarios,time for path planning is always limited,which is a challenge known as the anytime problem.Anytime planners address this by finding a collision-free path quickly and then improving it until time runs out,making UAVs more adaptable to different mission scenarios.However,current anytime algorithms based on A^(*)have insufficient control over the suboptimality bounds of paths and tend to lose their anytime properties in environments with large concave obstacles.This paper proposes a novel anytime path planning algorithm,Anytime Radiation A^(*)(ARa A^(*)),which can generate a series of suboptimal paths with improved bounds through decreasing search step sizes and can generate the optimal path when time is sufficient.The ARa A^(*)features two main innovations:an adaptive variable-step-size mechanism and elliptic constraints based on waypoints.The former helps achieve fast path searching in various environments.The latter allows ARa A^(*)to control the suboptimality bounds of paths and further enhance search efficiency.Simulation experiments show that the ARa A^(*)outperforms Anytime Repairing A^(*)(ARA^(*))and Anytime D^(*)(AD^(*))in controlling suboptimality bounds and planning time,especially in environments with large concave obstacles.Final flight experiments demonstrate that the paths planned by ARa A^(*)can ensure the safe flight of quadrotors.
文摘提出了一种新的Anytime分类算法,anytime averaged probabilistic under mutual information estimators(AAPMIE)。该分类算法能较好地适用于需要即时响应的在线业务。从信息论的角度认为每个属性所携带的信息量是不同的,对其他属性影响较大的属性应该具有较高的权限被优先选择作为super-parent参加分类计算,这样,有助于提高分类开始阶段的分类准确率,有助于在较少的计算资源下返回更好的分类效率。实验验证了该算法能在anytime分类的早期较好的改善分类效果降低分类的0-1损失错误率,伴随计算资源的增加,算法能进一步得到更好的分类准确率。
文摘ZTE provides customized CDMA WLL solutions that can bring youvalue-added services under any circumstances.Flexibility:Flexible network solutions for both urban and rural areas.Expertise:Cost-effective solutions based on CDMA2000 technology,offering wireless data services, can easily evolve to 3G.Experience:Proven technology with 90% market share in China aswell as applications in overseas countries like India and Brazil.
