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Dynamic Three-Dimensional Lift Planning for Intelligent Boom Cranes

IEEE-ASME TRANSACTIONS ON MECHATRONICS 2023年第5期28卷 2885-2896页

作者： Zhang, Zheshuo Zhang, Bangji Hu, Wen Zhou, Rui Cao, Dongpu Yin, Hui Zhejiang Univ City Coll Intelligent Transportat Syst Res Ctr Hangzhou 310000 Peoples R China Tsinghua Univ Sch Vehicle & Mobil Beijing 100080 Peoples R China Macau Univ Sci & Technol Macau 99908 Peoples R China Waytous Inc Qingdao 266100 Peoples R China Hunan Univ Coll Mech & Vehicle Engn Changsha 410082 Peoples R China

Manually planning a crane's lifting path is complicated and laborious since it typically depends on the planner's experience. We examined dynamic three-dimensional lift planning, including problem formulation for multiobjective planning and problem-solving with an improved A* algorithm. First, we quantified various feasible movements by introducing energy and time consumption models to determine the most efficient and quickest path. Second, we examined a new method for determining the visible lifting path in Configuration space (C-space) and derived an obstacle enveloping method for collision detection in C-space. Our method is both safe and feasible. Finally, we proposed an improved A* algorithm for lift planning considering multiple objectives and featuring better computational efficiency. The experimental and simulation results demonstrate that the proposed lift planning method can comprehensively consider multiple objectives, thus providing a high-quality path for actual lifting. Furthermore, compared with the ordinary A* algorithm, the improved A* algorithm had better computational efficiency and consumed less energy and time. To our best knowledge, this is the first novel algorithm for planning crane lifts considering energy consumption and visibility in C-space.

关键词： Cranes Planning Costs Safety Heuristic algorithms Energy consumption Kinetic energy Boom crane energy conservation graph search algorithm lift planning

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CAGviz: A Visual Analysis Method to Explore Cyber Asset graphs of Cybercrime Gangs 40th

CAGviz: A Visual Analysis Method to Explore Cyber Asset Grap...

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40th Computer graphics International Conference (CGI)

作者： Liu, Yinuo Li, Yifan Zhao, Binhao Zhou, Tianyi Chen, Shengtao Dong, Xiaoju Shanghai Jiao Tong Univ SJTU Paris Elite Inst Technol Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Univ Michigan Shanghai Jiao Tong Univ Joint Inst Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Environm Sci & Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Dept Comp Sci Shanghai 200240 Peoples R China

ISBN: (纸本)9783031500749;9783031500756

In recent decades, cybercrime has become more and more frequent in people's lives, causing serious consequences. Cybercrime groups usually hold a range of large and complex cyber assets to support the operation of their industries. Analyzing information about the cyber assets and the relationships among them can help people better understand the mechanism of cybercrime gangs. In this paper, based on an open-source cybercrime gang asset dataset, we propose a visual analysis system: CAGviz. The system helps to achieve tasks such as mining subgraphs of gang assets and extracting important assets. In addition, it also allows users to interactively view and analyze cyber asset information through a visual interface. Finally, a scenario analysis and user studies illustrate the effectiveness of the system.

关键词： Visual analytics Cyber asset graph search algorithm Interaction design

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Research on Travel Route Planning Optimization based on Large Language Model 6

Research on Travel Route Planning Optimization based on Larg...

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6th International Conference on Data-Driven Optimization of Complex Systems (DOCS)

作者： Li, Bohang Zhang, Kai Sun, Yiping Zou, Jianke Shopee Pte Ltd Dept Data Sci Singapore Singapore JP Morgan Quantitat Res New York NY USA Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China Peking Univ HSBC Business Sch Dept Management Beijing Peoples R China

ISBN: (纸本)9798350377859;9798350377842

In a trip planning service, travelers first set a starting point, a destination, and a sequential list of specific points of interest types (e.g., museums, restaurants, and parks). Based on this information, the service searches the spatial database to customize the best travel itinerary for the tourist. However, in previous studies, planners only considered the time factor when designing the optimal route, and failed to fully consider the quality of each point of interest. In this study, we specifically leveraged the capabilities of large language model to parse and respond to complex travel-related user queries. To apply large language model to route planning, we fine-tuned the model to understand geotagging and user travel preferences. We have introduced a novel graph search algorithm combined with large language model output, which optimizes the route search process to provide optimal travel recommendations by taking into account various factors such as distance length, budget constraints, and popularity of tourist attractions. In addition, we have integrated real-time traffic data and historical travel data to further improve the prediction accuracy and application usefulness of the model. In the experimental validation phase, we designed a series of benchmarks to compare the performance of the system with traditional algorithms and other machine learning-based route planning methods. Experimental results show that our model has a significant improvement compared with traditional methods in improving the speed and accuracy of path selection.

关键词： Travel route planning Large language model graph search algorithm Route optimization

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Method for Extracting Suspected Faulty Equipment Through Recursive Use of GNN Model 23

Method for Extracting Suspected Faulty Equipment Through Rec...

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23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)

作者： Sakuma, Seiji Sato, Ryosuke Nakamura, Mizuto Yamagoe, Kyoko NTT Corp NTT Network Innovat Ctr Network Operat Project Tokyo Japan

ISBN: (数字)9784885523397

ISBN: (纸本)9784885523397

Telecommunications carriers have investigated automating network operations such as failure recovery over the years. When a failure occurs, a large number of alarms (ALMs) are generated from multiple sets of equipment. However, the issuing of ALMs and the number of ALMs change dynamically depending on the situation. Therefore, in order to identify a suspected failure, the scope of the investigation must be specified based on the network topology and the combination of ALMs as a preliminary step. The workflow of such network operations is difficult to define, and efficiently selecting the range to investigate the failure is necessary for rapid failure recovery. However, automating such processes is difficult because in existing search algorithms defining in advance the solution that will terminate a search or conditions under which the search will be completed is impossible. In this paper, we propose a network node search algorithm that uses a graph neural network (GNN) to determine repeatedly the necessity for investigating neighboring equipment to determine the scope of the failure investigation in the network.

关键词： Network Operation Operation Automation GNN (graph Neural Network) graph search algorithm

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A Data-Based System for the Optimization of Emergency Medical Services Allocation in Rural Countries 27

A Data-Based System for the Optimization of Emergency Medica...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Guarino, Giulia Bernabucci, Ivan Bibbo, Daniele Caviglia, Marta Ambai, Amara J. Putoto, Giovanni Ragazzoni, Luca Tognon, Francesca Vandy, Matthew Jusu Barone-Adesi, Francesco Schmid, Maurizio Roma Tre Univ DIIEM Rome Italy INAIL DCOD Rome Italy Univ Piemonte Orientale CRIMEDIM Novara Italy Govt Sierra Leone MoHS Freetown Sierra Leone CUAMM Doctors Africa Padua Italy

ISBN: (纸本)9781665497923

Choosing the optimal positioning of Emergency Medical Services (EMS) base stations is needed to provide timely assistance in emergency conditions. In rural countries, this is obtained through a tiered system, where ambulances take charge of patients from specific gathering centres, and then take them to the hospitals. Here, a dynamic programming technique based on Dijkstra's algorithm has been devised to optimally allocate EMS to different base stations, based on location and travelling times for the paths leading to gathering centres and hospitals. The system, implemented in Java, has been tested on in-silico data simulating different scenarios of network connectivity, and validated against experimental data of EMS calls managed from the national EMS in Sierra Leone in 2021. The system allows to predict the average travel times to reach hospital facilities as a function of the number of ambulances and Base stations used.

关键词： graph search algorithm emergency medical service dynamic programming ambulances

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Drivable Path Planning Using Hybrid search algorithm Based on E* and Bernstein-Bezier Motion Primitives

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第8期51卷 4868-4882页

作者： Klancar, Gregor Seder, Marija Blazic, Saso Skrjanc, Igor Petrovic, Ivan Univ Ljubljana Fac Elect Engn SI-1000 Ljubljana Slovenia Univ Zagreb Fac Elect Engn & Comp Zagreb 10000 Croatia

This article proposes a hybrid path-planning algorithm, the HE* algorithm, which combines the discrete grid-based E* search and continuous Bernstein-Bezier (BB) motion primitives. Several researchers have addressed the smooth path planning problem and the sample-based integrated path planning techniques. We believe that the main benefits of the proposed approach are: directly drivable path, no additional post-optimization tasks, reduced search branching, low computational complexity, and completeness guarantee. Several examples and comparisons with the state-of-the-art planners are provided to illustrate and evaluate the main advantages of the HE* algorithm. HE* yields a collision-safe and smooth path that is close to spatially optimal (the Euclidean shortest path) with a guaranteed continuity of curvature. Therefore, the path is easily drivable for a wheeled robot without any additional post-optimization and smoothing required. HE* is a two-stage algorithm which uses a direction-guiding heuristics computed by the E* search in the first stage, which improves the quality and reduces the complexity of the hybrid search in the second stage. In each iteration, the search is expanded by a set of BBs, the parameters of which adapt continuously according to the guiding heuristics. Completeness is guaranteed by relying on a complete node mechanism, which also provides an upper bound for the calculated path cost. A remarkable feature of HE* is that it produces good results even at coarse resolutions.

关键词： Path planning Mobile robots Angular velocity Smoothing methods Collision avoidance Splines (mathematics) Bernstein-Bezier (BB) curve graph search algorithm hybrid planner motion primitives path planning

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A novel line segment detection algorithm based on graph search 10

A novel line segment detection algorithm based on graph sear...

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10th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Automatic Target Recognition and Navigation

作者： Zhao Hong-dan Liu Guo-ying Song Xu Anyang Normal Univ Dept Comp & Informat Engn Anyang 455002 Peoples R China

ISBN: (数字)9781510617209

ISBN: (纸本)9781510617209;9781510617193

To overcome the problem of extracting line segment from an image, a method of line segment detection was proposed based on the graph search algorithm. After obtaining the edge detection result of the image, the candidate straight line segments are obtained in four directions. For the candidate straight line segments, their adjacency relationships are depicted by a graph model, based on which the depth-first search algorithm is employed to determine how many adjacent line segments need to be merged. Finally we use the least squares method to fit the detected straight lines. The comparative experimental results verify that the proposed algorithm has achieved better results than the line segment detector (LSD).

关键词： line segment detection graph search algorithm graph model edge detection

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BetaDL: A protein beta-sheet predictor utilizing a deep learning model and independent set solution

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COMPUTERS IN BIOLOGY AND MEDICINE 2019年 104卷 241-249页

作者： Dehghani, Toktam Naghibzadeh, Mahmoud Eghdami, Mandie Ferdowsi Univ Mashhad Dept Comp Engn Mashhad Iran

The sequence-based prediction of beta-residue contacts and beta-sheet structures contain key information for protein structure prediction. However, the determination of beta-sheet structures poses numerous challenges due to long-range beta-residue interactions and the huge number of possible beta-sheet structures. Recently gaining attention has been the prediction of residue contacts based on deep learning models whose results have led to improvement in protein structure prediction. In addition, to reduce the computational complexity of determining beta-sheet structures, it has been suggested that this problem be transformed into graph-based solutions. Consequently, the current work proposes BetaDL, a combination of a deep learning and a graph-based beta-sheet structure predictor. BetaDL adopts deep learning models to capture beta-residue contacts and improve beta-sheet structure predictions. In addition, a graph-based approach is presented to model the beta-sheets conformational space and a new score function is introduced to evaluate beta-sheets. Furthermore, the present study demonstrates that the beta-sheet structure can be predicted within an acceptable computational time by the utilization of a heuristic maximum weight independent set solution. When compared to state-of-the-art methods, experimental results from BetaSheet916 and BetaSheet1452 datasets indicate that BetaDL improves the accuracy of beta-residue contact and beta-sheet structure prediction. Using BetaDL, beta-sheet structures are predicted with a 4% and 6% improvement in the F1-score at the residue and strand levels, respectively. BetaDL's source code and data are available at http://***/***/datasets/#BetaDL.

关键词： Protein structure prediction Deep learning model Contact map Beta-sheet structure graph search algorithm Independent set

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Mixed path planning for multi-robots in structured hospital environment

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JOURNAL OF ENGINEERING-JOE 2019年第14期2019卷 512-516页

作者： Huang, Xianqun Cao, Qixin Zhu, Xiaoxiao Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

Multi-robots are used in hospital for the delivery service. To increase the delivery efficiency, an appropriate multi-robots path planning algorithm is required. This study explains a mixed path planning algorithm for multi-robots in structured hospital environment which combines the 'corridor path planning' and 'room path planning', 'corridor path planning' uses graph search algorithm to plan the path in corridor for multiple hospital robots, and it uses the strongly connected digraph to describe corridor environment, so it could simplify the multi-robots path planning problem. While the 'room path planning' uses the artificial potential field method to plan the path in room for multiple hospital robots, it makes the hospital robot move flexibly in the room, so the robot could avoid the obstacle and other robots more flexibly. The algorithm is tested by simulation, and the result shows that mixed path planning algorithm makes the robot move fast in the corridor environment and move flexibly in the room environment.

关键词： mobile robots directed graphs robot vision collision avoidance hospitals search problems service robots path planning multi-robot systems medical robotics structured hospital environment mixed path planning algorithm corridor path room path graph search algorithm multiple hospital robots corridor environment multirobots path planning problem hospital robot move room environment multirobot path planning algorithm

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Combining discrete and continuous optimization to solve kinodynamic motion planning problems

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OPTIMIZATION AND ENGINEERING 2016年第3期17卷 533-556页

作者： Landry, Chantal Welz, Wolfgang Gerdts, Matthias Zurich Univ Appl Sci Technikumstr 9 CH-8401 Winterthur Switzerland Tech Univ Berlin Str 17 Juni 136 D-10623 Berlin Germany Univ Fed Armed Forces Werner Heisenberg Weg 39 D-85577 Neubiberg Germany

A new approach to find the fastest trajectory of a robot avoiding obstacles, is presented. This optimal trajectory is the solution of an optimal control problem with kinematic and dynamic constraints. The approach involves a direct method based on the time discretization of the control variable. We mainly focus on the computation of a good initial trajectory. Our method combines discrete and continuous optimization concepts. First, a graph search algorithm is used to determine a list of intermediate points. Then, an optimal control problem of small size is defined to find the fastest trajectory that passes through the vicinity of the intermediate points. The resulting solution is the initial trajectory. Our approach is applied to a single body mobile robot. The numerical results show the quality of the initial trajectory and its low computational cost.

关键词： Trajectory planning Optimal control problem Collision avoidance graph search algorithm Initialization Robotics

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