Unmanned aerial vehicles have been developed and applied to support agricultural production management.Compared with piloted aircraft,an Unmanned Aerial Vehicle(UAV)can focus on small crop fields at lower flight altit...Unmanned aerial vehicles have been developed and applied to support agricultural production management.Compared with piloted aircraft,an Unmanned Aerial Vehicle(UAV)can focus on small crop fields at lower flight altitudes than regular aircraft to perform site-specific farm management with higher precision.They can also“fill in the gap”in locations where fixed winged or rotary winged aircraft are not readily available.In agriculture,UAVs have primarily been developed and used for remote sensing and application of crop production and protection materials.Application of fertilizers and chemicals is frequently needed at specific times and locations for site-specific management.Routine monitoring of crop plant health is often required at very high resolution for accurate site-specific management as well.This paper presents an overview of research involving the development of UAV technology for agricultural production management.Technologies,systems and methods are examined and studied.The limitations of current UAVs for agricultural production management are discussed,as well as future needs and suggestions for development and application of the UAV technologies in agricultural production management.展开更多
Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developmen...Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.展开更多
文摘Unmanned aerial vehicles have been developed and applied to support agricultural production management.Compared with piloted aircraft,an Unmanned Aerial Vehicle(UAV)can focus on small crop fields at lower flight altitudes than regular aircraft to perform site-specific farm management with higher precision.They can also“fill in the gap”in locations where fixed winged or rotary winged aircraft are not readily available.In agriculture,UAVs have primarily been developed and used for remote sensing and application of crop production and protection materials.Application of fertilizers and chemicals is frequently needed at specific times and locations for site-specific management.Routine monitoring of crop plant health is often required at very high resolution for accurate site-specific management as well.This paper presents an overview of research involving the development of UAV technology for agricultural production management.Technologies,systems and methods are examined and studied.The limitations of current UAVs for agricultural production management are discussed,as well as future needs and suggestions for development and application of the UAV technologies in agricultural production management.
基金supported by the National Natural Science Foundation of China(61403158,61520106008)the Project of the Education Department of Jilin Province(2016-429)
文摘Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.
