Artificial Intelligence and Robotics Commons^™

Real-Time Simulation Method Of Ultra-High-Definition Video Texture, Yangyang Liu, Gangyi Ding, Dapeng Yan, Tong Xue

Journal of System Simulation

Abstract: With the development and promotion of ultra-high-definition video technology, how to quickly simulate ultra-high-definition video texture has gradually become an important research issue. Aiming at the completeness and high efficiency of simulation, a real-time simulation method of ultra-high-definition video texture is proposed to improve the video texture quality and display frequency simultaneously. A fast generation method of video texture based on GPU parallel is designed, which solves the time-consuming problem of decoding and transcoding. An efficient data transmission method based on shared texture is proposed. On the basis of the simulation engine, the real-time simulation system of ultra-high-definition video …

Research On Nested Named Entity Recognition In Missile Field Text, Jingwen Guan, Xiao Song, Xiaoqing Li, Tong Yang, Junhua Zhou

Journal of System Simulation

Abstract: Compared with the text recognition in conventional fields, it is difficult to recognize the large number of nested named entities in professional terms. This is also one of the care challenges in building the knowledge graph in aerospace field. For the named entity recognition technologies, bidirectional long short-term memory network plus conditional random field (BiLSTM-CRF) is often used to identify entities, which is difficult to distinguish the complex relationships such as nesting and intersection of terms in missile field. In order to solve the problem, based on the nested entity labeling of domain text, a nested named entity recognition …

Robot Path Planning By Fusing Particle Swarm Algorithm And Improved Grey Wolf Algorithm, Menglong Cao, Wenbin Zhao, Zhiqiang Chen

Journal of System Simulation

Abstract: Aiming at the long paths and slow convergence speed of GWO algorithm in robot path planning, a hybrid PSO-GWO algorithm based on PSO algorithm and the improved GWO algorithm is proposed. By running PSO algorithm for many times, the initial wolf group size and initial fitness value are determined. A nonlinear convergence factor is introduced to balance the exploration and development capabilities of GWO algorithm, and a dynamic inertia weight factor is proposed to ensure the leadership system of alpha wolf and to promote the population communication. Levy flight and greedy strategy are used to effectively avoid the local …

Lidar Slam Mapping Method Adapted To Environmental Spatial Changes, Songming Jiao, Xin Yao, Hui Ding, Yufei Zhong

Journal of System Simulation

Abstract: In the environment with obvious changes in space size, aiming at the drift and other problems of the existing algorithm, Adp-lio-sam mapping method is proposed to adapt to the environment space changes, and improve the generality of lio-sam algorithm. Point cloud dewarping method is improved, and Kalman filter algorithm is used to carry out the motion compensation data by fusing lidar interframe pose interpolation and IMU interpolation. Fuzzy algorithm is used to adapt different points filtering thresholds for different spatial environments and the constraints of loop closure detection are optimized. Experimental results show that, compared with the existing …

Research On Modeling And Optimization Method Of Torpedo Anti-Jamming Attack Based On Game Confrontation, Liqiang Guo, Ma Liang, Zhang Hui, Yang Jing, Fan Xueman, Cheng Zhuo

Journal of System Simulation

Abstract: Aiming at the strong adversarial characteristics of underwater attack and defense operations and the time-consuming problem of traditional Monte Carlo method, a model of torpedo anti-jamming attack based on game confrontation is designed and an improved genetic simulated annealing algorithm for optimal model is proposed. Through the research method of simulation analysis, on the basis of the models of two torpedo salvo attack and submarine acoustic resistance defense, the attack-defense confrontation model is constructed according to the Nash equilibrium theory under zero-sum game. The initial population, fitness function, and evolutionary strategy of GA are improved by the ideas of …

Target Search Planning And Algorithm For Monitoring Of Polar Disaster Areas, Fei Ding, Meinan Zhang, Hengheng Zhuang, Hairong Ma

Journal of System Simulation

Abstract: Aiming at improving the ability of safe navigation route planning and risk assessment of ships in polar waters, a target search model and method based on clustering and efficient indexing of monitoring center are proposed. By constructing a disaster monitoring scenario based on the current navigation area of the ship, a virtual electronic fence is introduced to define the monitoring area. Spectral clustering algorithm is used to divide the risk level of the fence area, extract high-risk areas, and optimize the generation of target search scenarios; Efficient determination of the matching relationship between the target vessel and the fence …

Two-Stage Robust Optimization-Based Economic Dispatch Of Virtual Power Plants Considering Cogeneration, Jinpeng Liu, Peng Jinchun, Jiaming Deng, Hushihan Liu

Journal of System Simulation

Abstract: With continuous enrichment of resources of the supply side and flexible and changeable load of the demand side of energy system to effectively cope with the complexity of system operation optimization and resource allocation, a robust optimization model of virtual power plant considering the interaction between electric and thermal units is proposed. Considering the uncertainty of renewable energy and load in virtual power plant, a two-stage robust optimization model of min-max-min structure is established, and the optimal operation economy dispatching scheme in the worst scenario is obtained. Robustness coefficient is introduced to flexibly adjust the conservativeness of the optimization …

Energy Management Strategy Of Multi-Agent Microgrid Based On Q-Learning Algorithm, Miaomiao Ma, Lipeng Dong, Xiangjie Liu

Journal of System Simulation

Abstract: This paper proposes a multi-agent microgrid energy management method for the energy trading and benefit distribution in the microgrid power market based on the Q-learning algorithm. Based on the electricity market, microgrid system and transaction process are constructed to clarify the responsibilities of each unit. The mathematical models of distributed power generations are established by considering the changes in wind speed, light intensity and ambient temperature, as well as the upper and lower limit constraints of the output power of each power generation unit. On this basis, the distributed power generations and user loads are regarded as agents, and …

Modeling And System Realization Of Assembly Robot Based On Digital Twin, Jian Xu, Xin Song, Xiuping Liu, Bo Chen

Journal of System Simulation

Abstract: Aiming at the problems of time-consuming, labor-intensive and poor accuracy in programming of complex operations of industrial assembly robots, an online programming method for robots based on digital twin is proposed. From the four dimensions of geometry, contact dynamics, behavior and rules, the faithful mapping of the robot from real to virtual space is realized. The verification of multi-part assembly trajectory planning program, real-time synchronous operation and state monitoring are realized. An assembly robot modeling and online programming system based on digital twin is designed and built. A six-axis industrial robot cell is taken as an example to verify …

Detection Of False Data Injection Attack In Smart Grid Based On Improved Ukf, Lisheng Wei, Qian Zhang

Journal of System Simulation

Abstract: Due to the disruption and threat of false data injection attack (FDIA) on grid cyber-physical systems (GCPS), and to address the problem that false data is difficult to be detected, a method for smart grid false data detection based on weighted least squares (WLS) and improved unscented Kalman filter (UKF) is proposed. FDIA is modeled mathematically, and the residual analysis shows that the FDIA is difficult to be detected. In the case of the injection attack vector, the improved UKF is applied to state estimation. Meanwhile, the state estimation of the system is performed by the WLS, which is …

Modeling And Identification Of Wind Power Generation System Based On Hammerstein Model, Feng Li, Tian Zheng, Wei Song

Journal of System Simulation

Abstract: A modeling and identification method of wind power generation system based on Hammerstein model is studied to establish high-precision model of wind power generation system. Firstly, 3σ criterion is used to propose the abnormal data, and the eliminated data is used to train the nominal model of the wind power generation system. Furthermore, the Hammerstein model is used to establish the data-driven model of wind power generation system, and the combined signal composed of separable signal and actual wind speed is used as the input of the Hammerstein model. The output of the separable signal through the nominal model …

Simulation Of Pedestrian Emergency Evacuation Considering Terrorist Attack Mode, Shuchao Cao, Jialong Qian

Journal of System Simulation

Abstract: To investigate pedestrian evacuation under the sudden terrorist attack, an evacuation model is established for pedestrians taking into account the terrorist attack mode. The terrorist can take two strategies including attacking the nearest pedestrian and attacking the crowd in the model. The evacuation time, casualties and location distribution in various scenarios under different attack modes are analyzed. The results show that pedestrians need to maintain a proper escape intention when avoiding the terrorist. The closer the initial position of the terrorists to the exit, the greater the number of casualties and the longer the evacuation time. The effect of …

Improved Particle Swarm Algorithm Of Unrelated Parallel Batch Scheduling Optimization, Lizhen Du, Tao Ye, Yuhao Wang, Yajun Zhang

Journal of System Simulation

Abstract: To address the problems of population diversity loss and the tendency to fall into local optimality in the PSO (particle swarm optimization)algorithm in dealing with unrelated parallel batch scheduling problems, an improved scheduling optimization algorithm for PSO is proposed for minimizing the maximum completion time solution. A real number encoding based on the sequence of artifacts is used for the encoding operation. A new strategy based on J_B local search is designed based on the mixed integer programming model of the problem. The Metropolis criterion of the simulated annealing algorithm isintroduced into the individual extreme value search of the …

An Intelligent Driver Model Simulation Considering Both Backward Looking Effect And Velocity Difference, Yin Xu, Yun Pu, Haixu Liu, Yifan Tan

Journal of System Simulation

Abstract: Aiming at the phenomenon that driver adjusts vehicle movement by observing the following vehicles through rearview mirror in the actual car-following driving, an improved intelligent driver model accounting for both backward looking effect and velocity difference is proposed, and the critical stability condition of the new model is obtained by employing the linear stability analysis. Based on the numerical simulation experiments, the car following characteristics analysis during the acceleration process of the vehicle and the traffic safety evaluation are carried out. A small disturbance simulation under the periodic boundary condition is used to verify the conclusion consistency of stability …

Path Planning Of Mobile Robots Based On Memristor Reinforcement Learning In Dynamic Environment, Hailan Yang, Yongqiang Qi, Baolei Wu, Dan Rong

Journal of System Simulation

Abstract: In order to solve the path planning problem of mobile robots in dynamic environment, two-layer path planning algorithm based on improved ant colony algorithm and MA-DQN algorithm is proposed. Static global path planning is accomplished by ant colony algorithm that improved the probabilistic transfer function and the pheromone updating principle; the traditional DQN algorithm structure is improved by using the memristor as the synaptic structure of neural network, and then completed the local dynamic obstacle avoidance of the mobile robot. The path planning mechanism is switched according to whether there are dynamic obstacles within the sensing range of the …

Attack Decision-Making Model Of Armed Helicopter Based On Multi-Index Fuzzy Set, Chunyan Wang, Xiang Wang, Minchi Kuang, Danfeng Wu, Zhengtong Li

Journal of System Simulation

Abstract: Aiming at the attack decision-making task requirements of armed helicopters in uncertain battlefield environment, the constructed multi-index fuzzy set is quantitatively characterized by the improved Gaussian model. The strategic benefit value model is constructed by using the combat restraint relationship, and the target ranking set is obtained by dynamically assigning the weight factors of the threat value and the strategic benefit value to complete the attack decision-making. The results show that the proposed method can better use the threat index data in modeling, and can provide theoretical guidance and modeling reference to improve the decision-making advantage of armed …

Intelligent Path Planning For Mobile Robots Based On Sac Algorithm, Laiyi Yang, Jing Bi, Haitao Yuan

Journal of System Simulation

Abstract: Aiming at the high dimension, slow convergence and complex modelling of traditional path planning algorithms for mobile robots, a new intelligent path planning algorithm is proposed, which is based on deep reinforcement learning soft actor-critic (SAC) algorithm to save the poor performance of robot in complicated environments with static and dynamic obstacles. An improved reward function is designed to enable mobile robots to quickly avoid obstacles and reach targets by using state dynamic normalization and priority experience pool techniques. To evaluate the performance, a pygame-based simulation environment is constructed. Compared with proximal policy optimization(PPO) algorithm, experimental …

Monitoring Method Research On Passenger Behavior On Escalator Based On Digital Twin, Nan Lü, Qibing Wang, Lu Jiawei, Juntong Chen, Gang Xiao

Journal of System Simulation

Abstract: In order to solve the problems that the traditional escalator cannot be monitored and analyzed in real time during operation, the management and maintenance only on escalator equipment side, and the lack of monitoring passenger dangerous behavior, a monitoring method of passenger behavior on escalator based on digital twin is proposed. By constructing the digital twin of escalators, a visual interface is designed to map the escalator running status and passenger behavior data. Through passenger video surveillance, the improved OpenPose posture recognition algorithm is used to obtain the key point data of human body. Posture recognition is classified to …

A Compliant Robot Control Based On Extended Social-Force Model For Human-Following And Obstacle Avoidance, Jianwei Peng, Zhelin Liao, Hanchen Yao, Zhiyu Wan, Liqi Zhu, Houde Dai

Journal of System Simulation

Abstract: Human-robot coexisting is an essential feature of the next generation mobile robot. A compliant robot control strategy based on the extended social-force model for human-following and obstacle avoidance in coexisting-cooperative-cognitive environment is presented. The human-following controller based on impedance control can simultaneously adjust human-robot interaction force and position deviation to carry out the compliant human-following of mobile robots. Considering humanrobot- obstacle interactions, based on the extended social-force model and proxemics, a control strategy for human-friendly compliant human-following and obstacle avoidance is designed to solve the obstacle avoidance problem of robot and ensure the human comfort and improving the social …

Machine Learning-Based Classification Of Chronic Traumatic Brain Injury Using Hybrid Diffusion Imaging, Jennifer Muller, Ruixuan Wang, Devon Middleton, Mahdi Alizadeh, Kichang Kang, Ryan Hryczyk, George Zabrecky, Chloe Hriso, Emily Navarreto, Nancy Wintering, Anthony J. Bazzan, Chengyuan Wu, Daniel A. Monti, Xun Jiao, Qianhong Wu, Andrew B. Newberg, Feroze Mohamed

Marcus Institute of Integrative Health Faculty Papers

BACKGROUND AND PURPOSE: Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging.

MATERIALS AND METHODS: A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging …