In order to deliver medical products (medicines, vaccines, blood packs, etc.) in time for needed areas, a method of transporting goods using drones is being studied. However, temperature-sensitive medical products may...In order to deliver medical products (medicines, vaccines, blood packs, etc.) in time for needed areas, a method of transporting goods using drones is being studied. However, temperature-sensitive medical products may decay due to outside temperature changes. The time required to transport over the distance may vary a lot as well. As a result, the likelihood of the goods deteriorating is very high. There is a need for a study on cargo bay to prevent this and to protect the medical goods. In this paper, in order to protect the temperature sensitive medical goods, the inside cargo bay is equipped with the cooling fan device and the electric heating elements. These elements can be monitored and controlled according to the user’s discretion. By using the web server built inside the cloud server, the temperature can be controlled in real-time from anywhere without the limitation of distance. We built the proposed device, and installed it on the drone cargo bay. The test results show that the cargo bay can be temperature-controlled, and the setting can be maintained over a great distance. The user can watch the temperature variations during the transport and ascertain the goodness of the medical supply with the data. It is expected that such development can greatly enhance the utility of the drone operations, especially for the medical supply transport applications.展开更多
Dynamic hand gesture recognition is a desired alternative means for human-computer interactions.This paper presents a hand gesture recognition system that is designed for the control of flights of unmanned aerial vehi...Dynamic hand gesture recognition is a desired alternative means for human-computer interactions.This paper presents a hand gesture recognition system that is designed for the control of flights of unmanned aerial vehicles(UAV).A data representation model that represents a dynamic gesture sequence by converting the 4-D spatiotemporal data to 2-D matrix and a 1-D array is introduced.To train the system to recognize designed gestures,skeleton data collected from a Leap Motion Controller are converted to two different data models.As many as 9124 samples of the training dataset,1938 samples of the testing dataset are created to train and test the proposed three deep learning neural networks,which are a 2-layer fully connected neural network,a 5-layer fully connected neural network and an 8-layer convolutional neural network.The static testing results show that the 2-layer fully connected neural network achieves an average accuracy of 96.7%on scaled datasets and 12.3%on non-scaled datasets.The 5-layer fully connected neural network achieves an average accuracy of 98.0%on scaled datasets and 89.1%on non-scaled datasets.The 8-layer convolutional neural network achieves an average accuracy of 89.6%on scaled datasets and 96.9%on non-scaled datasets.Testing on a drone-kit simulator and a real drone shows that this system is feasible for drone flight controls.展开更多
Our previous study shows that the lateral disturbance motion of a model drone fly does not have inherent stability （passive stability）,because of the existence of an unstable divergence mode.But drone flies are obse...Our previous study shows that the lateral disturbance motion of a model drone fly does not have inherent stability （passive stability）,because of the existence of an unstable divergence mode.But drone flies are observed to fly stably.Constantly active control must be applied to stabilize the flight.In this study,we investigate the lateral stabilization control of the model drone fly.The method of computational fluid dynamics is used to compute the lateral control derivatives and the techniques of eigenvalue and eigenvector analysis and modal decomposition are used for solving the equations of motion.Controllability analysis shows that although inherently unstable,the lateral disturbance motion is controllable.By feeding back the state variables （i.e.lateral translation velocity,yaw rate,roll rate and roll angle,which can be measured by the sensory system of the insect） to produce anti-symmetrical changes in stroke amplitude and/or in angle of attack between the left and right wings,the motion can be stabilized,explaining why the drone flies can fly stably even if the flight is passively unstable.展开更多
针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference ...针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival)无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory, DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution, TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。展开更多
文摘In order to deliver medical products (medicines, vaccines, blood packs, etc.) in time for needed areas, a method of transporting goods using drones is being studied. However, temperature-sensitive medical products may decay due to outside temperature changes. The time required to transport over the distance may vary a lot as well. As a result, the likelihood of the goods deteriorating is very high. There is a need for a study on cargo bay to prevent this and to protect the medical goods. In this paper, in order to protect the temperature sensitive medical goods, the inside cargo bay is equipped with the cooling fan device and the electric heating elements. These elements can be monitored and controlled according to the user’s discretion. By using the web server built inside the cloud server, the temperature can be controlled in real-time from anywhere without the limitation of distance. We built the proposed device, and installed it on the drone cargo bay. The test results show that the cargo bay can be temperature-controlled, and the setting can be maintained over a great distance. The user can watch the temperature variations during the transport and ascertain the goodness of the medical supply with the data. It is expected that such development can greatly enhance the utility of the drone operations, especially for the medical supply transport applications.
文摘Dynamic hand gesture recognition is a desired alternative means for human-computer interactions.This paper presents a hand gesture recognition system that is designed for the control of flights of unmanned aerial vehicles(UAV).A data representation model that represents a dynamic gesture sequence by converting the 4-D spatiotemporal data to 2-D matrix and a 1-D array is introduced.To train the system to recognize designed gestures,skeleton data collected from a Leap Motion Controller are converted to two different data models.As many as 9124 samples of the training dataset,1938 samples of the testing dataset are created to train and test the proposed three deep learning neural networks,which are a 2-layer fully connected neural network,a 5-layer fully connected neural network and an 8-layer convolutional neural network.The static testing results show that the 2-layer fully connected neural network achieves an average accuracy of 96.7%on scaled datasets and 12.3%on non-scaled datasets.The 5-layer fully connected neural network achieves an average accuracy of 98.0%on scaled datasets and 89.1%on non-scaled datasets.The 8-layer convolutional neural network achieves an average accuracy of 89.6%on scaled datasets and 96.9%on non-scaled datasets.Testing on a drone-kit simulator and a real drone shows that this system is feasible for drone flight controls.
基金supported by the National Natural Science Foundation of China (10732030)the 111 Project (B07009)
文摘Our previous study shows that the lateral disturbance motion of a model drone fly does not have inherent stability （passive stability）,because of the existence of an unstable divergence mode.But drone flies are observed to fly stably.Constantly active control must be applied to stabilize the flight.In this study,we investigate the lateral stabilization control of the model drone fly.The method of computational fluid dynamics is used to compute the lateral control derivatives and the techniques of eigenvalue and eigenvector analysis and modal decomposition are used for solving the equations of motion.Controllability analysis shows that although inherently unstable,the lateral disturbance motion is controllable.By feeding back the state variables （i.e.lateral translation velocity,yaw rate,roll rate and roll angle,which can be measured by the sensory system of the insect） to produce anti-symmetrical changes in stroke amplitude and/or in angle of attack between the left and right wings,the motion can be stabilized,explaining why the drone flies can fly stably even if the flight is passively unstable.
文摘针对低空经济发展涉及的安全管理问题,在总结低空经济相关技术路线原理及落地方案的运行经验,分析低空安防普适性的4个建设方案:雷达与通感一体技术融合方案、广播式自动相关监视技术方案、远程识别技术方案和基于TDOA(time difference of arrival)无线电技术的多源融合方案的基础上,构建无人飞行器探测技术评价指标体系,并建立了一种基于决策试验评估实验室(decision-making trial and evaluation laboratory, DEMATEL)和优劣解距离法(technique for order preference by similarity to an ideal solution, TOPSIS)的多属性评价方法。结果发现,以TDOA为基础的多源融合方案是构建城市低空安防体系的有效路径和普适性方案。研究表明,低空安防体系的建设是一个系统性工程,需要政府、企业和社会各方的共同努力,在技术、数据、运营等多个层面进行整合,以适应未来低空经济的发展需求。
