2002~2022年北京大气气溶胶光学特性的地基遥感连续观测

长时间序列的气溶胶光学特性观测资料是定量研究气溶胶辐射和气候效应的重要基础,也是空气质量和环境健康研究的重要数据来源。本文系统评述了全球AERONET(Aerosol Robotic Network)观测网,并介绍了我国最长观测时间的AEROENT北京站发展状况和一些研究成果;使用北京站长达20余年的观测数据,针对AERONET观测网的光学辐射产品的多时间尺度变化特征进行系统分析,讨论了长期观测的重要性和迫切性。

Decentralized Searching of Multiple Unknown and Transient Radio Sources with Paired Robots

In this paper, we develop a decentralized algorithm to coord inate a group of mobile robots to search for unknown and transient radio sources. In addition to limited mobility and ranges of communication and sensing, the robot team has to deal with challenges from signal source anonymity, short transmission duration, and variable transmission power. We propose a two-step approach: First, we decentralize belief functions that robots use to track source locations using checkpoint-based synchronization, and second, we propose a decentralized planning strategy to coordinate robots to ensure the existence of checkpoints. We analyze memory usage, data amount in communication, and searching time for the proposed algorithm. We have implemented the proposed algorithm and compared it with two heuristics. The experimental results show that our algorithm successfully trades a modest amount of memory for the fastest searching time among the three methods.

Quantum Cooperative Robotics and Autonomy

The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper.The two areas are brought together in establishing an interdisciplinary interface that contributes to advancing the field of system autonomy,and pushes the engineering boundaries beyond the existing techniques.The present research adopts the experimental aspects of quantum entanglement and quantum cryptography,and integrates these established quantum capabilities into distributed robotic platforms,to explore the possibility of achieving increased autonomy for the control of multi-agent robotic systems engaged in cooperative tasks.Experimental quantum capabilities are realized by producing single photons(using spontaneous parametric down-conversion process),polarization of photons,detecting vertical and horizontal polarizations,and single photon detecting/counting.Specifically,such quantum aspects are implemented on network of classical agents,i.e.,classical aerial and ground robots/unmanned systems.With respect to classical systems for robotic applications,leveraging quantum technology is expected to lead to guaranteed security,very fast control and communication,and unparalleled quantum capabilities such as entanglement and quantum superposition that will enable novel applications.

Relay switched, scalable topology control for mobile robot networks based on motion synchronization

A mobile robot network is said to be easily scalable to any number of robots if its performance is kept almost fixed after these robots are added or some fail in the network. An interaction dynamics model based on motion synchronization is first established. Considering the mobility of mobile robot networks, we propose a relay switched, distributed topology control for the scalable network to drive neMy added robots to the most suitable positions with more neighbors as well as self-heal the blank positions of failed robots, and give a metric of the topology structure for evaluating the performance of network topologies. Then, we prove the stability of motion synchronization with the individual control based on Lyapunov exponent. Finally, the results of simulations have demonstrated the validity of the proposed modeling and control methods.

Robots in Ecology:Welcome to the machine

Robots have primarily been developed for warfare, yet they also serve peaceful purposes. Their use in ecology is in its infancy, but they may soon become essential tools in a broad variety of ecological sub-disciplines. Autonomous robots, in particular drones sent to previously inaccessible areas, have revolutionized data acquisition, not only for abiotic parameters, but also for recording the behavior of undisturbed animals and collecting biological material. Robots will also play an essential role in population ecology, as they will allow for automatic census of individuals through image processing, or via detection of animals marked electronically. These new technologies will enable automated experimentation for increasingly large sample sizes, both in the laboratory and in the field. Finally, interactive robots and cyborgs are becoming major players in modern studies of animal behavior. Such rapid progress nonetheless raises ethical, environmental, and security issues.

IQABC-Based Hybrid Deployment Algorithm for Mobile Robotic Agents Providing Network Coverage

Working as aerial base stations,mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target area.Herein,a challenging issue is how to deploy these mobile robotic agents to provide network services with good quality for more users,while considering the mobility of on-ground devices.In this paper,to solve this issue,we decouple the coverage problem into the vertical dimension and the horizontal dimension without any loss of optimization and introduce the network coverage model with maximum coverage range.Then,we propose a hybrid deployment algorithm based on the improved quick artificial bee colony.The algorithm is composed of a centralized deployment algorithm and a distributed one.The proposed deployment algorithm deploy a given number of mobile robotic agents to provide network services for the on-ground devices that are independent and identically distributed.Simulation results have demonstrated that the proposed algorithm deploys agents appropriately to cover more ground area and provide better coverage uniformity.

Characteristic model-based consensus of networked heterogeneous robotic manipulators with dynamic uncertainties

In this paper, we address the characteristic model-based discrete-time consensus problem of networked robotic manipulators with dynamic uncertainties. The research objective is to achieve joint-position consensus of multiple robotic agents interconnected on directed graphs containing a spanning tree. A novel characteristic model-based distributed adaptive control scenario is proposed with a state-relied projection estimation law and a characteristic model-based distributed controller. The performance analysis is also unfolded where the uniform ultimate boundedness(UUB) of consensus errors is derived by resorting to the discrete-time-domain stability analysis tool and the graph theory. Finally, numerical simulations illustrate the effectiveness of the proposed theoretical strategy.

Analysis and Evaluation of the Global Aerosol Optical Properties Simulated by an Online Aerosol-coupled Non-hydrostatic Icosahedral Atmospheric Model

Aerosol optical properties are simulated using the Spectral Radiation Transport Model I~）r Aerosol Species （SPRINTARS） coupled with the Non-hydrostatic ICosahedral Atmospheric Model （NICAM）. The 3-year global mean all-sky aerosol optical thickness （AOT） at 550 nm, theAngstr/Sm Exponent （AE） based on AOTs at 440 and 870 nm, and the single scattering albedo （SSA） at 550 nm are estimated at 0.123, 0.657 and 0.944, respectively. For each aerosol species, the mean AOT is within the range of the AeroCom models. Both the modeled all-sky and clear-sky results are compared with observations from the Moderate Resolution Imaging Spectroradiometer （MODIS） and the Aerosol Robotic Network （AERONET）. The simulated spatiotemporal distributions of all-sky AOTs can generally reproduce the MODIS retrievals, and the correlation and model skill can be slightly improved using the clear-sky results over most land regions. The differences between clear-sky and all-sky AOTs are larger over polluted regions. Compared with observations from AERONET, the modeled and observed all-sky AOTs and AEs are generally in reasonable agreement, whereas the SSA variation is not well captured. Although the spatiotemporal distributions of all-sky and clear-sky results are similar, the clear-sky results are generally better correlated with the observations. The clear-sky AOT and SSA are generally lower than the all-sky results, especially in those regions where the aerosol chemical composition is contributed to mostly by sulfate aerosol. The modeled clear-sky AE is larger than the all-sky AE over those regions dominated by hydrophilic aerosol, while the＇opposite is found over regions dominated by hydrophobic aerosol.

Warehouse automation by logistic robotic networks:a cyber-physical control approach

In this paper we provide a tutorial on the background of warehouse automation using robotic networks and survey relevant work in the literature.We present a new cyber-physical control method that achieves safe,deadlock-free,efficient,and adaptive behavior of multiple robots serving the goods-to-man logistic operations.A central piece of this method is the incremental supervisory control design algorithm,which is computationally scalable with respect to the number of robots.Finally,we provide a case study on 30 robots with changing conditions to demonstrate the effectiveness of the proposed method.

Navigation of Non-holonomic Mobile Robot Using Neuro-fuzzy Logic with Integrated Safe Boundary Algorithm

In the present work, autonomous mobile robot（AMR） system is intended with basic behaviour, one is obstacle avoidance and the other is target seeking in various environments. The AMR is navigated using fuzzy logic, neural network and adaptive neurofuzzy inference system（ANFIS） controller with safe boundary algorithm. In this method of target seeking behaviour, the obstacle avoidance at every instant improves the performance of robot in navigation approach. The inputs to the controller are the signals from various sensors fixed at front face, left and right face of the AMR. The output signal from controller regulates the angular velocity of both front power wheels of the AMR. The shortest path is identified using fuzzy, neural network and ANFIS techniques with integrated safe boundary algorithm and the predicted results are validated with experimentation. The experimental result has proven that ANFIS with safe boundary algorithm yields better performance in navigation, in particular with curved/irregular obstacles.

Scene images and text information‐based object location of robot grasping

With the rapid development of artificial intelligence(AI),the application of this technology in the medical field is becoming increasingly extensive,along with a gradual increase in the amount of intelligent equipment in hospitals.Service robots can save human resources and replace nursing staff to achieve some work.In view of the phenomenon of mobile service robots'grabbing and distribution of patients'drugs in hospitals,a real‐time object detection and positioning system based on image and text information is proposed,which realizes the precise positioning and tracking of the grabbing objects and completes the grasping of a specific object(medicine bottle).The lightweight object detection model NanoDet is used to learn the features of the grasping objects and the object category,and bounding boxes are regressed.Then,the images in the bounding boxes are enhanced to overcome unfavourable factors,such as a small object region.The text detection and recognition model PP‐OCR is used to detect and recognise the enhanced images and extract the text information.The object information provided by the two models is fused,and the text recognition result is matched with the object detection box to achieve the precise posi-tioning of the grasping object.The kernel correlation filter(KCF)tracking algorithm is introduced to achieve real‐time tracking of specific objects to precisely control the robot's grasping.Both deep learning models adopt lightweight networks to facilitate direct deployment.The experiments show that the proposed robot grasping detection system has high reliability,accuracy and real‐time performance.

Retrievals of aerosol optical depth and total column ozone from Ultraviolet Multifilter Rotating Shadowband Radiometer measurements based on an optimal estimation technique

A Bayesian optimal estimation （OE） retrieval technique was used to retreive aerosol optical depth （AOD）, aerosol single scattering albedo （SSA）, and an asymmetry factor （g） at seven ultraviolet wavelengths, along with total column ozone （TOC）, from the measurements of the UltraViolet Multifilter Rotating Shadowband Radiometer （UV-MFRSR） deployed at the Southern Great Plains （SGP） site during March through November in 2009. The OE technique specifies appropriate error covariance matrices and optimizes a forward model （Tropospheric ultraviolet radiative transfer model, TUV）, and thus provides a supplemental method for use across the network of the Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） for the retrieval of aerosol properties and TOC with reasonable accuracy in the UV spectral range under various atmo- spheric conditions. In order to assess the accuracy of the OE technique, we compared the AOD retreivals from this method with those from Beer＇s Law and the AErosol RObotic Network （AERONET） AOD product. We also examine the OE retrieved TOC in comparison with the TOC from the U.S. Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） and the Ozone Monitoring Instrument （OMI） satellite data. The scatterplots of the estimated AOD from the OE method agree well with those derived from Beer＇s law and the collocated AERONET AOD product, showing high values of correlation coefficients, generally 0.98 and 0.99, and large slopes, ranging from 0.95 to 1.0, as well as small offsets, less than 0.02 especially at 368 nm. The comparison of TOC retrievals also indicates the promising accuracy of the OE method in that the standard deviations of the difference between the OE derived TOC and other TOC products are about 5 to 6 Dobson Units （DU）. Validation of the OE retrievals on these selected dates suggested that the OE technique has its merits and can serve as a supplemental tool in further analyzing UVMRP data.

Comparison of aerosol optical depth of UV-B Monitoring and Research Program （UVMRP）, AERONET and MODIS over continental United States

The concern about the role of aerosols as to their effect in the Earth-Atmosphere system requires observation at multiple temporal and spatial scales. The Moderate Resolution Imaging Spectroradiameters （MODIS） is the main aerosol optical depth （AOD） monitoring satellite instrument, and its accuracy and uncertainty need to be validated against ground based measurements routinely. The comparison between two ground AOD measurement programs, the United States Department of Agriculture （USDA） Ultmviolet-B Monitoring and Research Program （UVMRP） and the Aerosol Robotic Network （AERONET） program, confirms the consistency between them. The intercomparison between the MODIS AOD, the AERONET AOD, and the UVMRP AOD suggests that the UVMRP AOD measurements are suited to be an alternative ground-based validation source for satellite AOD products. The experiments show that the spatial-temporal dependency between the MODIS AOD and the UVMRP AOD is positive in the sense that the MODIS AOD compare more favorably with the UVMRP AOD as the spatial and temporal intervals are increased. However, the analysis shows that the optimal spatial interval for all time windows is defined by an angular subtense of around 1° to 1.25°, while the optimal time window is around 423 to 483 minutes at most spatial intervals. The spatial-temporal approach around 1.25° ＆ 423 minutes shows better agreement than the prevalent strategy of 0.25° ＆ 60 minutes found in other similar investigations.