Operations Research, Systems Engineering and Industrial Engineering Commons^™

Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan

Journal of System Simulation

Abstract: Due to the complexity and variability of the desert environment, the key to the high-efficient of mobile robot is how to avoid obstacles and plan its path. To solve the problems of poor search efficiency and slow convergence of deep reinforcement learning algorithm in complex environment, an improved deep reinforcement learning path planning algorithm is proposed. The exploration factor is improved and dynamically adjusted according to the convergence degree of the algorithm, so that the exploration factor dynamically decreases with the increase of the understanding degree of the agent to the environment, thus speeding up the convergence speed of …

A Talking Cart, Abdullah Bin Naeem

LSU New Orleans Theses and Dissertations

This research investigates the development of a robust AI-powered detection and tracking engine aimed at revolutionizing the retail checkout experience. The foundation of this work is a comprehensive exploration of state-of-the-art Computer Vision methodologies, particularly focusing on object detection, segmentation, and tracking. The study employs a modular pipeline that integrates advanced visual recognition algorithms with a robust data processing framework.

Key to this work is the construction of a synthetic dataset using Unity3D, enabling the generation of high-quality annotated data that mirrors real-world retail scenarios. This approach addresses the challenge of insufficient labeled datasets by simulating diverse and cluttered shopping …

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …

A Method For Key Node Identification In Operational Target System Based On War Gaming, Yongfu Zhang, Yang Liu, He Yuan

Journal of System Simulation

Abstract: The identification of key nodes in an operational target system is an important basis for combat command decision-making. Due to the lack of experimental verification of key node identification in the current operational target system in a campaign-level dynamic confrontation environment, a complex network model of operational target system with large-scale entities and complex interaction relationship was constructed by taking integrated air defense network as an example, with the help of the data derived from the large joint war gaming; the characteristics of wargame data were considered, and the value characteristics of combat targets and network structure characteristics were …

Platform Path Optimization Method Based On Cumulative Detection Probability Of Sonar Search, Xiang Wei, Xingxuan Liu, Dianzheng Fu, Tianji Yang, Jiaxuan Yang

Journal of System Simulation

Abstract: To address the lack of research on the optimal path of mobile search platform to search for moving targets, this paper proposes a path optimization method of mobile search platform based on cumulative search probability theory. Based on the cumulative detection probability (CDP), one of the important criteria of sensor performance evaluation, a single-peak CDP calculation formula is constructed by using a time series correlation model, namely the (λ, σ) process model. A set of target motion scenarios are constructed, and the trajectory probability of target scenarios and their CDP at different time are corrected by Bayesian posterior probability. …

Modeling For Decision Support Of Flight Ground Support Process, Zhiwei Xing, Ruiwen Yu, Biao Li, Zhaoxin Chen

Journal of System Simulation

Abstract: Aiming at the problems of insufficient decision-making ability and low operational efficiency of the flight ground support process, a decision support model of the flight ground support process based on the department of defense architecture framework (DoDAF) is proposed. Starting from the support operation, support resources, and the relationship between them, the quantitative description of the flight ground support process is performed. DoDAF and the model-based systems engineering (MBSE) modeling method are combined to establish a decision support model of the flight ground support process. The decision utility function is established to analyze the utility value of the comprehensive …

End-To-End Motion Planning Of Unmanned Vehicles Based On Multimodal Deep Reinforcement Learning, Kaiyuan Ding, Askar Hamdulla, Bin Zhu, Eksan Firkat, Zhengtang Ma

Journal of System Simulation

Abstract: Since the agent cannot sense the surrounding environment and cannot successfully avoid obstacles, reinforcement learning fails to be generalized to robot motion planning in difficult terrain. Therefore, a solution based on multimodal deep reinforcement learning, which learns to blend proprioceptive states with high-dimensional depth sensor inputs, is proposed for the motion planning of unmanned vehicles. To be specific, proprioceptive states offer contact measurement for immediate reaction, and the unmanned vehicle can learn and forecast environmental changes with its attached visual sensors, proactively navigating around obstacles and uneven terrains numerous time steps ahead. TransProAct (transformer-based proactive action), a unique end-to-end …

Flexible Job Shop Scheduling Method Based On Collaborative Agent Reinforcement Learning Algorithm, Jian Li, Huankun Li, Pengbo He, Huabei Wang, Liping Xu, Kui He

Journal of System Simulation

Abstract: To enhance the efficiency of flexible job shop scheduling, this paper develops a Markov decision process with specific constraints tailored to the scheduling problem. A cooperative agent reinforcement learning method is proposed to solve the problem of concurrent selection of workpieces and machines. During the construction of the Markov decision process, a disjunctive graph is introduced to represent the state characteristics. Two agents are introduced to select the workpieces and machines. The reward parameters governing the entire scheduling process are established by predicting variations in the minimum-maximum completion time across different time points. A GIN(graph isomorphic network) graph neural …

Dual-Resource Constrained Distributed Flexible Scheduling For Aerospace Structural Components, Yufang Wang, Dianqing Zhang, Xiaolin Hua, Binbin Yao, Fan Chen

Journal of System Simulation

Abstract: A dual-resource constrained distributed flexible job-shop scheduling model was established by taking into account the worker constraints of the finishing process and the requirements of distributed multi-factory collaboration in the production of aerospace structural components. A hybrid grey wolf optimization algorithm based on the critical factory was proposed to solve this problem. The model contained four subproblems: factory selection, operation sequencing, machine selection, and worker selection. In view of these four sub-problems, a four-layer coding and a new decoding method were designed to avoid the use conflict of machines and workers. In addition, a new mechanism for hunting and …

Automatic Detection Algorithm For Typical Defects Of Substation Based On Improved Yolov5, Zhongkai Xu, Yanling Liu, Xiaojuan Sheng, Chao Wang, Wenjun Ke

Journal of System Simulation

Abstract: In response to the challenges present in the context of defect recognition in substations, such as complex substation defects and sample imbalance, an improved YOLOv5 algorithm was proposed. The Transformer model was introduced into the YOLOv5 network structure, leveraging the self-attention mechanism to capture long-range dependencies among features. A focal loss-based optimization was employed to improve the loss function, as well as the detection accuracy and robustness of defects of small sample substations. To meet the requirements of substation defect recognition, a dedicated dataset was constructed. A clustering algorithm was applied to the real annotation boxes to generate more …

Object Detection Of Lightweight Transformer Based On Knowledge Distillation, Gaihua Wang, Kehong Li, Qian Long, Jingxuan Yao, Bolun Zhu, Zhengshu Zhou, Xuran Pan

Journal of System Simulation

Abstract: In autonomous driving, the efficiency and accuracy of object detection are significant. Object detection based on Transformer structure has gradually become the mainstream method, eliminating the complex anchor generation and non-maximum suppression (NMS). It has problems of high computing cost and slow convergence. An object detection model of the based lightweight pooling transformer (LPT) is designed, which contains a pooling backbone network and dual pooling attention mechanism. A general knowledge distillation method is intended for the DETR (detection transformer) model, which transfers prediction results, query vector, and features extracted by the teacher as knowledge to the LPT model to …

A Hybrid Genetic Search Algorithm For Capacitated Electric Vehicle Routing Problem, Dongyao Jin, Mi Liu, Yena Zhu, Yijiang Zhao

Journal of System Simulation

Abstract: The capacitated electric vehicle routing problem (CEVRP) is an NP-hard combinatorial optimization problem in logistics distribution, aiming to minimize the total delivery distance of electric vehicles while satisfying carrying capacity and battery charge constraints. A hybrid genetic search algorithm is proposed to solve CEVRP by decomposing it into two subproblems: capacitated vehicle routing problem (CVRP) and fixed-route vehicle charging problem (FRVCP). A coding scheme with a two-layer chromosome structure is designed to represent the decision variables of these two subproblems. A Split operation is employed to generate vehicle routes for solving CVRP, and five neighborhood search operators, including Relocate, …

Traffic Sign Recognition Model With Long-Tail Distribution Based On Yolox-Tiny, Yunpeng Wu, Yingxiong Fu, Lijun Shen, Feng Cui

Journal of System Simulation

Abstract: Accurate recognition of traffic signs plays an important role in the field of intelligent driving. Traffic sign training datasets with long-tail distribution increase the difficulty of traffic sign recognition. A traffic sign recognition model with long-tail distribution based on YOLOX-Tiny was proposed to improve the poor performance of the model trained on long-tail distribution datasets. A long-tail traffic sign dataset was created based on the TT100K_2021 (tsinghua-tencent 100K 2021) dataset. YOLOX-Tiny was chosen as the underlying model by considering picture numbers in datasets, sample distribution, and model size. Equalization loss v2 (EQL v2) was used as classification loss to …

Real-Time Lidar Slam Algorithm Based On Distribution Optimal Registration, Weigang Li, Chuxiang Yu, Yongqiang Wang, Shaofeng Zou

Journal of System Simulation

Abstract: When scanning the surrounding environment, a lidar will generate some cluttered and sparse point cloud, which will cause excessive distribution fitting errors and correlation distances in the registration process, thus affecting the accuracy of the registration algorithm and the effect of simultaneous localization and mapping (SLAM). To address this problem, a real-time lidar SLAM algorithm based on distribution optimal registration is proposed. An eigenspectrum filter is designed, which takes the normalized minimum eigenvalue as the filtering object to filter out the points that do not match the set distribution in order to reduce the distribution fitting error. Secondly, a …

Research On Green Job Shop Scheduling Based On Herd Immunity Optimizer, Xunde Ma, Li Bi, Junjie Wang

Journal of System Simulation

Abstract: In view of the green flexible job shop scheduling problem where machines have multiple speeds, a green flexible job shop scheduling model under multiple speeds was constructed to minimize the makespan and total energy consumption under different speeds. A discrete coronavirus herd immunity optimizer (DCHIO) was proposed for a solution. A discrete individual updating method was introduced for the relatively large solution space of the multi-speed problem, based on which a population updating mechanism with multi-scale joint search was proposed to search the solution space quickly and uniformly. A dynamic mutation operation was designed to enhance the population diversity …

Agv Scheduling Problem At Automated Terminals Based On Improved Dqn Algorithm, Chengji Liang, Shidong Zhang, Yu Wang, Bin Lu

Journal of System Simulation

Abstract: A future tasks considering deep Q-network (F-DQN) algorithm was proposed to output realtime scheduling results of automated guided vehicles (AGVs) at automated terminals. This algorithm combined the advantages of real-time scheduling and static scheduling, improving the system status by considering static future task information when making real-time decisions, so as to obtain a better scheduling solution. In this study, the actual layout and equipment conditions of the Yangshan phase IV automated terminal were considered, and a series of simulation experiments were conducted using the Plant Simulation software. The experimental results show that the F-DQN algorithm can effectively solve the …

Global-Local Fusion For Efficient 3d Object Detection, Bin Lu, Minghan Wang, Yang Sun, Zhenyu Yang

Journal of System Simulation

Abstract: As the 3D object detection based on point clouds shows an incapacity of feature extraction and incongruity between classification and regression, this research introduces a novel ResCST architecture based on the SECOND network. It incorporates residual connections into the 3D sparse convolutional layer, with the advantages of capturing long-distance dependent relation by SwinTransformer and obtaining local features by convolutional neural network integrated, proposing the CNN-SwinTransformer hybrid model for enhanced feature extraction. It introduces the RCIoU method for the joint optimization of classification and regression tasks. The experimental results show that the model achieves a 3D detection accuracy of 91.21%, …

Optimization Of Crucial Targets For Air Defense Based On Combined Weighting-Topsis Model, Peng Zhang, Ke Feng

Journal of System Simulation

Abstract: To optimize the selection of crucial defended targets in regional air defense operations and improve the selection accuracy, this paper constructs a factor model considering the importance of air defense targets from the perspectives of target value, defense urgency, target vulnerability, and target recovery. Under the optimization of the TOPSIS method through a combination of the ANP and entropy weight methods, tendentious opinions of commanders and the excessive reliance on objective data can be overcome to ensure the factor weighting is more reasonable and accurate; Super Decisions is used to calculate the weights of the ANP method, accelerating data …

Eecbs Multi-Robot Path Planning Based On Variable Suboptimal Factors Of Prioritizing Conflicts, Xingyu Yan, Niya Wang, Jianlin Mao, Zhigang He, Dayan Li

Journal of System Simulation

Abstract: In the process of multi-robot path planning (MRPP), the unavoidable key conflicts between the optimal paths have a significant impact on the efficiency of path solving. To address this issue, an MRPP method based on variable suboptimal factors of prioritizing conflicts (PC) was proposed. Path search was performed at the lower layer of the explicit estimation conflict-based search (EECBS) algorithm; in the upper layer of the EECBS algorithm framework, the PC was determined, and the suboptimal factor of the robot with key conflicts was adaptively increased; by analyzing the distribution of obstacles in the surrounding neighborhoods of key conflicts, …

Slam Dynamic Algorithm Based On Improved Feature Description, Qiang Fu, Xianyun Teng, Yuanfa Ji, Fenghua Ren

Journal of System Simulation

Abstract: The original ORB descriptor algorithm has a low matching accuracy and long matching time, the positioning accuracy and robustness of the SLAM(simultaneous localization and mapping) system are severely disturbed by moving objects in dynamic scenes, and the ORB-SLAM3 system is incapable of constructing dense maps. To address the above problems, this paper proposes an improved ORB-SLAM3 based on the BEBLID descriptor and object detection. A lightweight YOLOv5s dynamic object detection network and dynamic feature removal module are fused with the tracking thread to improve the system's positioning accuracy. Replacing the original feature description algorithm, an improved local image descriptor …

Design And Implementation Of Maritime Unmanned Cross-Domain Collaborative Effectiveness Evaluation System Based On Mlp, Hongyu Hu, Tianzhu Gao, Haitao Gu

Journal of System Simulation

Abstract: In the face of the problem of evaluating the detection capability effectiveness of the maritime unmanned cross-domain collaborative system, it is necessary to study the evaluation indexes and evaluation algorithm. In this paper, the robot's own parameters and environmental parameters are combined to build a calculation model for evaluation indexes, such as detection coverage rate, repeated detection rate, the number of pixels per unit area, and energy as well as an evaluation system for detection capability of the maritime unmanned cross-domain collaborative system. The subjectivity in the evaluation process is reduced, and training data is generated by the availability …

Improvement Of A* Algorithm In Path Planning Of Mobile Robot, Dexin Yao, Hongjun San, Yaru Wang, Haijie Sun, Jiupeng Chen, Xiaoyuan Yang

Journal of System Simulation

Abstract: To solve the problems of excessively redundant nodes, low search efficiency, and excessive path turning angle in the path search of the traditional A* algorithm, an improved A* algorithm is proposed to plan the optimal path. First, the amount of search neighborhood of the A* algorithm is increased to 24 to obtain a more accurate and comprehensive search field. Second, the angle search algorithm is introduced, eliminating the unnecessary nodes in the path search and making the search more target-oriented. Third, the heuristic function is weighted by the exponential attenuation through the relative position of the current point and …

A Plugin-Based Unreal Engine Adapter For Hla-Based Distributed Simulation, Mei Yang, Peng Wang

Journal of System Simulation

Abstract: With the wide application of game engine-based simulation in transportation, military and other fields, the demand for interoperability between game engine and traditional simulations is becoming increasingly strong. For the HLA-based integration of Unreal Engine and the traditional simulations, a plugin-based Unreal Engine adapter for distributed simulation is designed, which enables the rapid development of Unreal Engine federate and the efficient integration. The simulation shows the feasibility of the plugin-based Unreal Engine adapter.

Research On Sequential Design Methods For Satellite Combat Simulation Tests, Yanlin Wang, Zhijun Cheng, Zichen Wang, Jian Zhong

Journal of System Simulation

Abstract: Aiming at the problem that satellite monitoring mission simulation tests cannot take into account the number of sample points and model accuracy in the complex test space, a hybrid sequential test design method for satellite simulation tests based on sample density and local nonlinearity is proposed. Voronoi division is used to describe the density of discrete point distribution, and the nonlinearity is measured with the help of Taylor expansion and sample point neighborhood gradient information. The two are combined to calculate the hybrid metrics, and the sample points are ranked and new ones are added until the stopping criterion …

Improving Nsga-Iii Algorithm For Solving High-Dimensional Many-Objective Green Flexible Job Shop Scheduling Problem, Yigang Xu, Yong Chen, Chen Wang, Yunxian Peng

Journal of System Simulation

Abstract: Aiming at the poor initial solution quality and low local search efficiency of NSGA-III in solving the many-objective flexible job shop scheduling model, an improved NSGA-III (NSGA-III-TV) is proposed. Based on MSOS encoding, the different mixed initialization strategies are adopted for OS and MS chromosomes to improve the quality of initial solutions. Based on the critical path, an improved N6 neighborhood structure is used for neighborhood search, which effectively reduce the completion time and reducing search randomness. Three effective mutation operators are employed to expand the search space and improve the convergence capability in the later stages. Test results …

Multi-Objective Energy-Efficient No-Wait Flow Shop Scheduling Based On Hybrid Discrete State Transition Algorithm, Cong Wang, Jiaying Yu, Hongli Zhang

Journal of System Simulation

Abstract: A hybrid discrete state transition algorithm (HDSTA) is designed to solve the energyefficient no-wait flow shop scheduling problem (EENWFSP) minimizing makespan and total energy consumption. According to the characteristics of the problem, the coding method of job sequence and speed matrix is designed, and the heuristic algorithm is used to obtain the high-quality initial solution. According to the properties of EENWFSP, solving and allocating four discrete operators. The swap, shift and symmetry operators are embedded in secondary state transition are used for job sequence optimization, and the substitute operators are used for machine speed optimization. The speed substitute strategy …

Adaptive Recognition Method Of Capability Boundary Parameters For Unmanned Autonomous Systems, Jinwen Li, Peng Wang, Youmei Pan, Xinyao Hui

Journal of System Simulation

Abstract: To effectively cope with the dimension curse in simulation testing and reduce the number of simulations times needed in the traditional full-space parameter traversal, it is necessary to obtain specific simulation data to accurately reflect the modeling characteristics of the test data to obtain the informative and representative samples of the original data with a smaller number of simulations. A digital simulation test model for adaptive recognition ;/of capability boundary parameters for UAS is proposed. The model is initially constructed with a good point set with a multi-weight structure; In combination with an adaptive kernel function boundary point recognition, …

Operational Effectiveness Analysis Method Based On Spherical Fibonacci Lattice, Weiran Guo, Jiahao Zhou, Xiang Huang, Xin Zhao

Journal of System Simulation

Abstract: An operational effectiveness modeling and computing method based on spherical Fibonacci lattice is proposed to address the low simulation accuracy and computational efficiency of large-scale sampling for traditional latitude and longitude grids. The formal description of operational effectiveness in command information systems and the generation method of spherical Fibonacci grid points are provided. A command information systems capability analysis framework is constructed, which focuses on ensuring the continuous mission support and uses the responsibility area of combat tasks as a reference. Through a top-down system design approach, a layered and decoupled combat effectiveness computing framework is proposed which studies …

Ground Robot Relocation Method Based On Uav Point Cloud Map, Hongzhi Huang, Kai Yan, Changfeng Liu, Jianwen Wang, Bin Luo

Journal of System Simulation

Abstract: In response to the challenge of relocalization in air-ground collaborative systems without the support of Global Navigation Satellite System (GNSS), and the associated issues of insufficient accuracy, a coarse-to-fine relocalization algorithm based on a three-dimensional point cloud map is proposed. The algorithm eliminates the influence of invalid point clouds from the sky and ground through index filtering, performs coarse localization by extracting global features from the point cloud and applying truncated least squares estimation, and then employs voxel-based iterative closest point (ICP) for precise optimization to obtain the more accurate localization results. A ground robot localization and autonomous navigation …

Research On Digital Twin Technology Of Coal Mine Tunneling Machine System, Xingwang Cai, Yaoqiang Pei, Jihua Yang, Ruifeng Pang

Journal of System Simulation

Abstract: Aiming at the problems in coal mine tunneling operations, including complex geological structures, harsh on-site conditions, low automation of excavation equipment, and frequent safety incidents, a digital twin solution is proposed. PLC as hardware core, MQTT protocol, and EMQX as foundation, through the integration of IoT, internet, digital twins, and virtual reality technologies, the mapping rules for parameter matrices and a fault cause analysis table are established, which realize the functions such as data collection, processing during excavation, data mapping between equipment and twin models, data storage, process simulation, remote control, intelligent fault detection, and early warning, and significantly …