Trajectory Optimization for a Cruising Unmanned Aerial Vehicle Attacking a Target at Back Slope While Subjected to a Wind Gradient

The trajectory of a tubular launched cruising unmanned aerial vehicle is optimized using the modified direct collocation method for attacking a target at back slope under a wind gradient. A mathematical model of the cruising unmanned aerial vehicle is established based on its operational and motion features under a wind gradient to optimize the trajectory. The motion characteristics of  “altitude adjustment” and “suicide attack” are taken into full account under the combat circumstance of back slope time key targets. By introducing a discrete time function, the trajectory optimization is converted into a nonlinear programming problem and the SNPOT software is applied to solve for the optimal trajectory of the missile under different wind loads. The simulation results show that, for optimized trajectories, the average attack time decreased by up to 29.1% and the energy consumption is reduced by up to 25.9% under specified wind gradient conditions. A, ωdire, and Wmax have an influence on the flight trajectories of cruising unmanned aerial vehicle. This verifies that the application of modified direct collocation method is reasonable and feasible in an effort to achieve more efficient missile trajectories

On compression rate of quantum autoencoders: Control design, numerical and experimental realization

Quantum autoencoders which aim at compressing quantum information in a low-dimensional latent space lie in the heart of automatic data compression in the field of quantum information. In this paper, we establish an upper bound of the compression rate for a given quantum autoencoder and present a learning control approach for training the autoencoder to achieve the maximal compression rate. The upper bound of the compression rate is theoretically proven using eigen-decomposition and matrix differentiation, which is determined by the eigenvalues of the density matrix representation of the input states. Numerical results on 2-qubit and 3-qubit systems are presented to demonstrate how to train the quantum autoencoder to achieve the theoretically maximal compression, and the training performance using different machine learning algorithms is compared. Experimental results of a quantum autoencoder using quantum optical systems are illustrated for compressing two 2-qubit states into two 1-qubit states

Spatial distribution of cultural ecosystem services demand and supply in urban and suburban areas: a case study from Shanghai, China

In the urban ecosystem, the demand for cultural ecosystem services (CES) has greatly increased, and the imbalance of CES supply and demand has been prominent. This paper integrated multi-source data to analyze and visualize the spatial differences in CES demand and supply capacity between Shanghai urban center and suburbs. Based on the geo-tagged photo data, the spatial distribution differences of the four types of CES demand, Recreation & tourism services (RTS) demand, Aesthetic services (AS) demand, Heritage & cultural services (HCS) demand, and Spiritual & religious services (SRS) demand, were analyzed. Residents and tourists had a strong demand for recreation and tourism, and the spatial agglomeration effect was the most obvious. Overall, CES demand was more concentrated in urban center, while the spatial distribution of suburbs was relatively discrete. At the same time, there were under supply areas of CES near the Huangpu River in urban center and suburbs. Results from bivariate Moran's I method showed: 1) there was a significant positive spatial correlation between CES demand and CES supply capacity in urban center; 2) CES supply had a positive external impact on CES demand; and 3) the increase in CES supply capacity can promote the growth of CES demand

Neo-tectonic Movement in the Pearl River Delta (PRD) Region of China and Its Effects on the Coastal Sedimentary Environment

This chapter presents the Late Quaternary neo-tectonic movement in the Pearl River Delta (PRD) region of China and its effects on the coastal sedimentary environment. Taking the Xilin Hill fault as the example, we have explained the reason of the PRD formation, inferred its interactions with local/regional climate and sea-level changes, and analyzed the evolution of the PRD formation and its controlling factors of the coastal sedimentary environment

Retina-Based Pipe-Like Object Tracking Implemented Through Spiking Neural Network on a Snake Robot

Vision based-target tracking ability is crucial to bio-inspired snake robots for exploring unknown environments. However, it is difficult for the traditional vision modules of snake robots to overcome the image blur resulting from periodic swings. A promising approach is to use a neuromorphic vision sensor (NVS), which mimics the biological retina to detect a target at a higher temporal frequency and in a wider dynamic range. In this study, an NVS and a spiking neural network (SNN) were performed on a snake robot for the first time to achieve pipe-like object tracking. An SNN based on Hough Transform was designed to detect a target with an asynchronous event stream fed by the NVS. Combining the state of snake motion analyzed by the joint position sensors, a tracking framework was proposed. The experimental results obtained from the simulator demonstrated the validity of our framework and the autonomous locomotion ability of our snake robot. Comparing the performances of the SNN model on CPUs and on GPUs, respectively, the SNN model showed the best performance on a GPU under a simplified and synchronous update rule while it possessed higher precision on a CPU in an asynchronous way