Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion pl...Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion planners is challenged.With the development of machine learning,the deep reinforcement learning(DRL)-based motion planner has gradually become a research hotspot due to its several advantageous feature.The DRL-based motion planner is model-free and does not rely on the prior structured map.Most importantly,the DRL-based motion planner achieves the unification of the global planner and the local planner.In this paper,we provide a systematic review of various motion planning methods.Firstly,we summarize the representative and state-of-the-art works for each submodule of the classical motion planning architecture and analyze their performance features.Then,we concentrate on summarizing reinforcement learning(RL)-based motion planning approaches,including motion planners combined with RL improvements,map-free RL-based motion planners,and multi-robot cooperative planning methods.Finally,we analyze the urgent challenges faced by these mainstream RLbased motion planners in detail,review some state-of-the-art works for these issues,and propose suggestions for future research.展开更多
As the surface conditions play a significant role on corona discharge and its related effects of the conductors,the influence of fine particulate matter on positive-polarity,direct-current conductors was studied exper...As the surface conditions play a significant role on corona discharge and its related effects of the conductors,the influence of fine particulate matter on positive-polarity,direct-current conductors was studied experimentally in this study.The surface morphologies of the conductor could be discovered from the experiments.The typical morphologies are the parallel chains of particles.To evaluate the surface condition quantitively,the surface roughness of the conductors is measured.It is found that the applied voltage and testing time have a great influence on the surface condition.After that,the corona characteristics of conductors are tested.It reveals that the total ground level electric field and ion flow density increases with the surface roughness growing.展开更多
基金supported by the National Natural Science Foundation of China (62173251)the“Zhishan”Scholars Programs of Southeast University+1 种基金the Fundamental Research Funds for the Central UniversitiesShanghai Gaofeng&Gaoyuan Project for University Academic Program Development (22120210022)
文摘Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion planners is challenged.With the development of machine learning,the deep reinforcement learning(DRL)-based motion planner has gradually become a research hotspot due to its several advantageous feature.The DRL-based motion planner is model-free and does not rely on the prior structured map.Most importantly,the DRL-based motion planner achieves the unification of the global planner and the local planner.In this paper,we provide a systematic review of various motion planning methods.Firstly,we summarize the representative and state-of-the-art works for each submodule of the classical motion planning architecture and analyze their performance features.Then,we concentrate on summarizing reinforcement learning(RL)-based motion planning approaches,including motion planners combined with RL improvements,map-free RL-based motion planners,and multi-robot cooperative planning methods.Finally,we analyze the urgent challenges faced by these mainstream RLbased motion planners in detail,review some state-of-the-art works for these issues,and propose suggestions for future research.
基金This work was financially supported by the National Natural Science Foundation of China(51377096,51877082)the Fok Ying-Tong Education Foundation,China grant no.151058,the Fundamental Research Funds for the Central Universities 2019MS011the Young Elite Scientists Sponsorship Program by CAST.
文摘As the surface conditions play a significant role on corona discharge and its related effects of the conductors,the influence of fine particulate matter on positive-polarity,direct-current conductors was studied experimentally in this study.The surface morphologies of the conductor could be discovered from the experiments.The typical morphologies are the parallel chains of particles.To evaluate the surface condition quantitively,the surface roughness of the conductors is measured.It is found that the applied voltage and testing time have a great influence on the surface condition.After that,the corona characteristics of conductors are tested.It reveals that the total ground level electric field and ion flow density increases with the surface roughness growing.
