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Entropy-based planning algorithm for Personalized Interventions: Preliminary Report on Question-reduction Agent 24

Entropy-based Planning Algorithm for Personalized Interventi...

ACM International Joint Conference on Pervasive and Ubiquitous Computing / ACM International Symposium on Wearable Computers (UbiComp/ISWC)

作者： Sano, Taiga Takahashi, Masami Fujimura, Kaori Inoue, Takafumi Sato, Tae Katagiri, Yurika NTT Social Informat Labs Yokosuka Kanagawa Japan

ISBN: (纸本)9798400710582

Prevention of lifestyle diseases is an important issue in terms of both the lifelong well-being of each individual and the burden on society. Although several artificial-intelligence-based chatbots have been proposed to support preventing such diseases, they have not yet reached a complex problem setting that combines multiple theories of behavioral change. In such complex settings, in addition to intervention selection, it is important to reduce the amount of attributes acquired to reduce the user's burden in preventing inhibition of motivation. Therefore, we developed the Entropy-Based planning algorithm that selects interventions from a small number of questions. To evaluate the algorithm, we conducted a short-term randomized control trial (RCT) with a small number of users as an initial validation. Due to certain limitations, we were unable to obtain results indicating sufficient effectiveness. However, important findings were obtained for the future development of behavioral-change support bots. The findings include the need to investigate the relevance of preferences among multiple behavior-change theories and balance the number of questions and accuracy of personalization on user impressions. We intend to conduct further research on the basis of these findings as well as conduct a large-scale RCT after improving the algorithm and experiment settings.

关键词： Healthcare Behavior Change User Burden planning algorithm

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Safety-field-based Path planning algorithm of Lane Changing for Autonomous Vehicles

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2022年第2期20卷 564-576页

作者： Lv, Xiaoxing Li, Weihua Wang, Jianfeng Harbin Inst Technol Weihai Sch Automot Engn Weihai Peoples R China

This study presents a novel planning approach of lane changing for autonomous vehicles to ensure multi-agent safety and comfortability in riding. First, a risk assessment model, Safety Field, combined with field theory and kinematics model was defined considering the passengers' subjective feelings to identify the long-term safety trends. Based on the safety field, a new planning algorithm named S algorithm was developed, which was inspired by the A* algorithm. The special grid map, the lists, and the evaluation function designed in the S algorithm enabling its application to complex dynamic situations while considering riding safety and riding comfort. And the proposed path planning method has good scalability that we extend its application scenarios from straight roads to curved roads. Finally, the S algorithm was validated in virtual traffic environments on straight and curved roads, and the results from the test cases demonstrated the effectiveness and scalability of the algorithm.

关键词： Autonomous vehicles lane changing planning algorithm safety field

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Design of Moving Target Detection System Based on planning algorithm 11th

Design of Moving Target Detection System Based on Planning A...

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11th International Conference on Applications and Techniques in Cyber Intelligence, ATCI 2023

作者： Qian, Hao Physical Education Teaching and Research Department Xinjiang University Xinjiang Urumqi830046 China

In order to detect moving targets in real time, it is necessary to establish a moving target detection system(MTDS) that can accurately identify them. This is very important in fields such as monitoring systems, autonomous driving, and intelligent robots. In order to improve the performance of the moving target detection system, this article believes that planning algorithms can be used. Therefore, this article uses the planning algorithm and points out that the planning algorithm can well schedule the internal resources of the MTDS and make intelligent decisions. Finally, this article conducts verification through comparative experiments. The results show that the average detection accuracy of the system based on the planning algorithm is 93.21%, while the average detection accuracy of the conventional system is 89.58%. The obvious gap proves that the planning algorithm can indeed improve the performance of the MTDS to a certain extent. © 2024 The Authors. Published by Elsevier B.V.

关键词： Intelligent Decision-Making Moving Target Detection Path planning planning algorithm

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Collaborative A*-Market-based Intelligent planning algorithm for Multi-Spraying Robots 35

Collaborative A*-Market-based Intelligent Planning Algorithm...

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35th Chinese Control and Decision Conference (CCDC)

作者： Liang, Le Chen, Yang-Yang Jiangsu Automat Res Inst Lianyungang 222006 Peoples R China Southeast Univ Sch Automat Nanjing 210096 Peoples R China

ISBN: (纸本)9798350334722

This paper addresses the cooperative path planning problem of multi-spraying robots with rectangular spraying areas, where obstacles are the rectangular spraying areas that are once completed. A novel collaborative A*-market-based planning algorithm is designed to achieve the cooperative path planning with obstacle avoidance. The optimal performance of the robot utilization, the short time and the low path cost are under consideration and achieved by the proposed A*-market planning algorithm. Three scenarios with the fixed starting points of each rectangular spraying area (that is, the upper left vertex, the upper right vertex, the lower left vertex and the lower right vertex) and without fixed starting points are given in simulation. It is indicated that the average time cost and the total distance cost in the case without fixed starting points are reduced by 7.93% and 15.54% as compared with the case with fixed starting points.

关键词： Path planning multi-spraying robots A*-market planning algorithm obstacle avoidance

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Design of Moving Target Detection System Based on planning algorithm

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Procedia Computer Science 2024年 247卷 647-653页

作者： Hao Qian Physical Education Teaching and Research Department Xinjiang University Urumqi 830046 Xinjiang China

关键词： planning algorithm Moving Target Detection Intelligent Decision-Making Path planning

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A Optimized NURBS Curve Trajectory planning algorithm Based on Genetic algorithm

A Optimized NURBS Curve Trajectory Planning Algorithm Based ...

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Chinese Automation Congress (CAC)

作者： Zhang, Chunyu Wang, Liwei Yu, Xinghu Tong, Mingsi Lin, Weiyang Gao, Huijun Harbin Inst Technol Sch Mechatron Engn Harbin Peoples R China Harbin Inst Technol Inst Intelligent Control & Syst Harbin Peoples R China HIT Ningbo Inst Intelligent Equipment Technol Ningbo Peoples R China

ISBN: (纸本)9781728176871

This article mainly designs a trajectory lanning algorithm for DELTA parallel robots. This algorithm is a timeoptimal trajectory planning algorithm. The space trajectory is based on the NURES Curves, that is, the curve equation is calculated after wo know the positions which the robot pass through in the space. Then use the genetic optimization algorithm to optimize the curve, get the optimized curve and then discretize the curve for interpolation calculation. At last we use the V-rep simulation software to simulate the algorithm, the similarity between the simulation trajectory and the calculation trajectory is very well, and the experiment proves that the algorithm is effective.

关键词： NURBS Curves formatting genetic optimization algorithm V-rep simulation time-optimal trajectory planning algorithm

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A Path planning algorithm for Plant Protection UAV for Avoiding Multiple Obstruction Areas

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IFAC-PapersOnLine 2018年第17期51卷 483-488页

作者： Yunling, Liu Zili, Xu Na, Li Shuxiang, Xu Gang, Yuan College of Information and Electrical Engineering China Agricultural University Beijing100083 China School of Technology Environments and Design University of Tasmania Tasmania7248 Australia

China's farmland environment is complex. The planting area often contains some irregular obstacles. It is hard for plant protection UAV (Unmanned Aerial Vehicle) to get good planning results to avoid obstacles automatically in the autonomous mode or only through sensors. In order to improve the application scope for plant UAVs with autonomous operation mode and to obtain good operation results, this paper proposes Multi-Obstacle Area Avoidance (MOAA) algorithm which is a path planning algorithm for avoiding obstacle areas. This algorithm is proposed based on the method of cattle ploughing reciprocation. According to the information of heading, spouting, operating areas and obstacle areas, the internal route of the spraying area is obtained. The order of lines and waypoints are determined by choosing the shortest route. And this algorithm uses the Ray method to avoid the polygon obstacles and multi-obstacle areas. Operating results of different obstacle zones and heading angles are tested through simulation experiments. The best optimization radio is 14.2% when obstacle area is 800m2. Then aiming at the problem of over-dispatching of routes in some cases, MOAA algorithm is further optimized. Actual optimization length in field experiments is 75 meters (optimization radio is 7.7%) when the heading angles is 315°. Field experimental results show that MOAA algorithm can select the best path scheme based on information such as obstacle height, area, *** it can improve the applicability of the plant protection UAV with autonomous operations. © 2018

关键词： Unmanned aerial vehicles (UAV) Antennas Autonomous operations Avoiding obstacle Obstacle Area Operating results Path planning algorithm Plant protection Route planning UAV (unmanned aerial vehicle)

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Generic Path planning algorithm for Mobile Robots Based on Bézier Curves

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IFAC-PapersOnLine 2016年第15期49卷 145-150页

作者： Costanzi, Riccardo Fanelli, Francesco Meli, Enrico Ridolfi, Alessandro Allotta, Benedetto Via di Santa Marta 3 Florence50139 Italy

The availability of an efficient and reliable path planning strategy is a great benefit to mobile robots. Being able to intelligently connect a series of waypoints is a crucial requirement for the execution of autonomous navigation tasks. Several performance indices can be used to evaluate the goodness of a path, including its length and smoothness. In this paper, the authors focus on planar path planning for mobile robots; Bézier curves are employed, optimizing the computed path with respect to length and curvature, the latter used as a measure of smoothness. Due to the complexity of the objective function, optimization is performed by means of a direct search method. The proposed approach aims at generating paths offering advantages to mobile robots navigation in terms of controllability and reducing the related power consumption. The performed tests show that the presented method allows to achieve interesting results, suggesting its viability as a suitable path planning strategy for different kinds of mobile robots. © 2016

关键词： Motion planning Air navigation Mobile robots Robot programming Robotics Autonomous navigation Direct search methods Objective functions Optimal trajectories Path planning algorithm Performance indices planning strategies Waypoints

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Multi-objective Particle Swarm Optimization algorithm for Feeder Capacity planning of Distribution Network Considering Dynamic Load 3

Multi-objective Particle Swarm Optimization Algorithm for Fe...

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3rd International Conference on New Energy and Power Engineering, ICNEPE 2023

作者： Yin, Xiang Liu, Jian Cheng, Shi Zang, Siqi State Grid Xinjiang Electric Power Co. Ltd. Urumqi830000 China Xinjiang Power Transmission and Transformation Co. Ltd. Urumqi830000 China

ISBN: (纸本)9798350393224

The optimization proportion of distribution network feeder capacity cannot reach the expected standard, so this paper proposes a multi-objective Particle swarm optimization algorithm for distribution network feeder capacity considering dynamic load. The multi-objective method is used to expand the planning scope, the multi-objective Particle swarm optimization feeder capacity planning matrix is set, and the feeder capacity optimization planning calculation model under dynamic load is designed. The experimental results show that the final optimization rate of the feeder capacity in the distribution network can reach over 5, indicating that the designed directional planning algorithm has high measurement accuracy, strong pertinence, and controllable error under dynamic load conditions and has practical application value. © 2023 IEEE.

关键词： Counting and dynamic load Distribution network Feeder capacity Multi-objective particle swarm Optimization planning planning algorithm

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Odor Source Localization in Obstacle Regions Using Switching planning algorithms with a Switching Framework

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SENSORS 2023年第3期23卷 1140页

作者： Luong, Duc-Nhat Kurabayashi, Daisuke Tokyo Inst Technol Dept Syst & Control Engn 2-12-1 OokayamaMeguro ku Tokyo 1528552 Japan

Odor source localization (OSL) robots are essential for safety and rescue teams to overcome the problem of human exposure to hazardous chemical plumes. However, owing to the complicated geometry of environments, it is almost impossible to construct the dispersion model of the odor plume in practical situations to be used for probabilistic odor source search algorithms. Additionally, as time is crucial in OSL tasks, dynamically modifying the robot's balance of emphasis between exploration and exploitation is desired. In this study, we addressed both the aforementioned problems by simplifying the environment with an obstacle region into multiple sub-environments with different resolutions. Subsequently, a framework was introduced to switch between the Infotaxis and Dijkstra algorithms to navigate the agent and enable it to reach the source swiftly. One algorithm was used to guide the agent in searching for clues about the source location, whereas the other facilitated the active movement of the agent between sub-environments. The proposed algorithm exhibited improvements in terms of success rate and search time. Furthermore, the implementation of the proposed framework on an autonomous mobile robot verified its effectiveness. Improvements were observed in our experiments with a robot when the success rate increased 3.5 times and the average moving steps of the robot were reduced by nearly 35%.

关键词： odor source localization planning algorithm olfactory robot algorithm switching

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