2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)最新文献_第9页

Risk-aware Energy Management of Extended Range Electric Delivery Vehicles with Implicit Quantile Network 基于隐式分位数网络的增程式电动运输车辆风险感知能量管理

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216797

Pengyue Wang, Yan Li, S. Shekhar, W. Northrop

{"title":"Risk-aware Energy Management of Extended Range Electric Delivery Vehicles with Implicit Quantile Network","authors":"Pengyue Wang, Yan Li, S. Shekhar, W. Northrop","doi":"10.1109/CASE48305.2020.9216797","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216797","url":null,"abstract":"Model-free reinforcement learning (RL) algorithms are used to solve sequential decision-making problems under uncertainty. They are data-driven methods and do not require an explicit model of the studied system or environment. Because of this characteristic, they are widely utilized in Intelligent Transportation Systems (ITS), as real-world transportation systems are highly complex and extremely difficult to model. However, in most literature, decisions are made according to the expected long-term return estimated by the RL algorithm, ignoring the underlying risk. In this work, a distributional RL algorithm called implicit quantile network is adapted for the energy management problem of a delivery vehicle. Instead of only estimating the expected long-term return, the full return distribution is estimated implicitly. This is highly beneficial for applications in ITS, as uncertainty and randomness are intrinsic characteristics of transportation systems. In addition, risk-aware strategies are integrated into the algorithm with the risk measure of conditional value at risk. In this study, we demonstrate that by changing a hyperparameter, the trade-off between fuel efficiency and the risk of running out of battery power during a delivery trip can be controlled according to different application scenarios and personal preferences.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132709873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Semi-Heuristic Approach for Tracking Buried Subsea Pipelines using Fluxgate Magnetometers 利用磁通门磁强计跟踪埋地海底管道的半启发式方法

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216755

Vibhav Bharti, David Lane, Sen Wang

引用次数: 2

Online Ranking of Physicians with Perishable Resources 易腐资源医师在线排名

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216858

Hanqi Wen, Xin Pan, Jie Song

{"title":"Online Ranking of Physicians with Perishable Resources","authors":"Hanqi Wen, Xin Pan, Jie Song","doi":"10.1109/CASE48305.2020.9216858","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216858","url":null,"abstract":"For the online healthcare platform, it is essential to recommend a list of physicians to arrived patients dynamically, in order to satisfy patients’ varied demands, improve the overall matching degree between patients and physicians as well as the resource allocation efficiency, since each physician only has limited registration capacity. In this paper we construct a general model to describe this dynamic ranking problem with patients’ rank-based choice behavior and limited resources. Under the framework of Markov Decision Process(MDP), the dynamic problem can be decomposed into a series of static problems as long as the marginal value of each physician’s registration resource can be approximated. To deal with the problem that at the cold-start stage the platform does not have available data to capture patients rank-based choice behavior specifically, we design a model-free LP-based method which can efficiently approximate the marginal value without requiring patients’ choice models as the input. We conduct a case study based on the data collected from the online healthcare platform to show how to apply this general framework in a real application and verify the capability of our methods.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114504889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model Predictive Control for Target Tracking in 3D with a Downward Facing Camera Equipped Fixed Wing Aerial Vehicle 固定翼飞行器下置摄像头三维目标跟踪的模型预测控制

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216801

Pravin Mali, A. Singh, M. Krishnal, P. Sujit

{"title":"Model Predictive Control for Target Tracking in 3D with a Downward Facing Camera Equipped Fixed Wing Aerial Vehicle","authors":"Pravin Mali, A. Singh, M. Krishnal, P. Sujit","doi":"10.1109/CASE48305.2020.9216801","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216801","url":null,"abstract":"In this paper, we consider the problem of tracking a ground vehicle with a fixed-wing aerial vehicle (FWV) equipped with a downward-facing camera. The complexity of the problem stems from the highly nonlinear kinematics of the FWV and the stall speed constraint. We propose a Model Predictive Control (MPC) approach for this problem that has two main contributions. Firstly, we model the tracking requirement through a novel constraint function that relates FWV’s position and orientation to the field of view of the camera. Secondly, we make a case for reformulating the underlying optimization of the MPC as an unconstrained problem and solving it through the state of the art gradient descent variants like ADAM and RMSProp. Specifically, we show the real-time performance of this optimizer while achieving good tracking performance under various kinematic constraints. We validate our MPC through extensive simulations, specifically highlighting the 3D spiral-like trajectories obtained for the FWV when tracking a slow-moving ground vehicle. We also present a quantitative analysis of the efficacy of the different gradient descent variants.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132052481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed and Synchronized Setup towards Real-Time Robotic Control using ROS2 on Linux 在Linux上使用ROS2实现机器人实时控制的分布式和同步设置

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9217010

Lennart Puck, Philipp Keller, Tristan Schnell, C. Plasberg, Atanas Tanev, G. Heppner, A. Rönnau, R. Dillmann

引用次数: 14

Simulating Polyculture Farming to Tune Automation Policies for Plant Diversity and Precision Irrigation 模拟混养耕作以调整植物多样性和精准灌溉的自动化政策

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216984

Yahav Avigal, Jensen Gao, William Wong, Kevin Li, G. Pierroz, F. Deng, M. Theis, Mark Presten, Ken Goldberg

引用次数: 10

Crowd stability analysis based on fluid resonance superposition principle and Lyapunov criterion 基于流体共振叠加原理和Lyapunov准则的人群稳定性分析

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216957

R. Zhao, Y. Wan, Qiong Liu, Daheng Dong, Cuiling Li

{"title":"Crowd stability analysis based on fluid resonance superposition principle and Lyapunov criterion","authors":"R. Zhao, Y. Wan, Qiong Liu, Daheng Dong, Cuiling Li","doi":"10.1109/CASE48305.2020.9216957","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216957","url":null,"abstract":"It is significant to analyze the stability of a crowd in public places to avoid possible confusion and dangerous accidents. This paper introduces fluid wave theory and regards the crowded groups as continuous media. Crowd panic propagation can be mapped into the spreading of fluid waves. In the case of emergencies, individual pedestrian’s emotion values are calculated by the panic propagation model. Based on the resonance and superposition principles of waves, this study converts emotion value into individual internal frequency. Considering the interaction between individuals, trust coefficient is defined to express the external equivalent frequency. Whether resonance occurs, with amplitude of negative emotion being amplified, can be judged through comparing the pedestrian internal frequency and the external equivalent frequency. In addition, Lyapunov criterion is applied to analyze the crowd stability from a system perspective. The flow chart of algorithm steps and implementation process are designed to realize application of wave superposition and resonance in crowd Stability. This study can further provide a more feasible program to observe the crowd in real time as well as guide evacuation decisions.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133499421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Flocking of Multi-Agent Systems with Uncertain Nonlinear Dynamics and Unknown Disturbances Using Neural Networks* 基于神经网络的不确定非线性动态和未知干扰的多智能体系统自适应群集研究*

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216754

Shiguang Wu, Z. Pu, J. Yi, Jinlin Sun, Tianyi Xiong, Tenghai Qiu

{"title":"Adaptive Flocking of Multi-Agent Systems with Uncertain Nonlinear Dynamics and Unknown Disturbances Using Neural Networks*","authors":"Shiguang Wu, Z. Pu, J. Yi, Jinlin Sun, Tianyi Xiong, Tenghai Qiu","doi":"10.1109/CASE48305.2020.9216754","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216754","url":null,"abstract":"Collective behavior of multi-agent systems brings some new problems in control theory and application. Especially, flocking problem of multi-agent systems with uncertain nonlinear dynamics and unknown external disturbances is a challenging problem. Some existing works assume that the intrinsic nonlinear dynamics of virtual leader is the same as those of the agents, which is unreasonable and impractical. To solve this issue, we consider an adaptive flocking problem of multi-agent systems with uncertain nonlinear dynamics and unknown external disturbances in this paper, where the intrinsic nonlinear dynamics of virtual leader is allowed to be different from the agents. Firstly, to approximate the uncertain nonlinear dynamics of each agent, an adaptive neural network is used, whose weights are updated online. Furthermore, an adaptive robust signal is designed to counteract the unknown external disturbances and neural network approximation errors, which is independent with the upper bound of the unknown external disturbances and neural network approximation errors. Moreover, an adaptive flocking control law is designed, which is proved that the flocking can be realized and the velocity errors converge to a small neighbor of the origin based on Lyapunov stability theory. Finally, the robustness and superiority of the proposed robust adaptive flocking control law are validated by two representative simulations.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125864740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Energy-Aware Multi-Goal Motion Planning Guided by Monte Carlo Search 蒙特卡罗搜索指导下的能量感知多目标运动规划

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9217008

Yazz Warsame, S. Edelkamp, E. Plaku

引用次数: 7

Robotic Harvesting of Asparagus using Machine Learning and Time-of-Flight Imaging – Overview of Development and Field Trials 利用机器学习和飞行时间成像的芦笋机器人收获-发展概况和田间试验

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9217006

M. Peebles, J. Barnett, M. Duke, S. Lim

引用次数: 1