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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

共 5311 条记录，以下是181-190 订阅

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Finite-time PID predictive control of networked control systems 17

Finite-time PID predictive control of networked control syst...

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17th international conference on control, automation, robotics and vision (ICARCV)

作者： Jiang, Tingting Park, Ju H. Zhang, Yuping Kong, Shaohua Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Sichuan Peoples R China Yeungnam Univ Dept Elect Engn Gyongsan 38541 South Korea Tibet Univ Sch Econ & Management Lhasa 850001 Tibet Peoples R China

ISBN: (纸本)9781665476874

this paper concerns the finite-time (FT) proportional-integral-derivative (PID) predictive control for networked control systems (NCSs) with time-varying delays. A PID networked predictive control (PID-NPC) method is first proposed. this method makes use of historical information and its error of prediction state. Furthermore, an augmented switched control system is established in which the switching signal is determined by the time delay. Sufficient conditions are derived so that the resulting systems are finite-time boundedness (FTB). then novel FT-PID controllers and the corresponding FT observers are given to compensate for the time-varying delays actively. Simulation example illustrates the effectiveness of the proposed method.

关键词： Networked control systems

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MultiVR: Digital Twin and Virtual Reality Based System for Multi-people Remote control Unmanned Aerial Vehicles 17

MultiVR: Digital Twin and Virtual Reality Based System for M...

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17th international conference on control, automation, robotics and vision (ICARCV)

作者： Chen, Haodong Liu, Fen Yang, Yuanlin Meng, Wei Guangdong Univ Technol Sch Automat Guangdong Prov Key Lab Intelligent Decis & Cooper Guangzhou 510006 Peoples R China

ISBN: (纸本)9781665476874

the remote control of Unmanned Aerial Vehicles (UAVs) in emergency rescues, large-scale search, e-commerce and other fields is still a hot topic. the majority of current remote human-computer interaction techniques, such as joysticks, monitoring interfaces, or gesture control, lack flexibility, have weak immersion, and have poor interaction. the study proposes the development of a novel system for controlling multiple UAVs using virtual reality (VR). A virtual system and a physical system make up the control system. A VR application uses a head-mounted display (HMD) to show the user a digital twin environment of a drone and a faraway location. the operators pilot the quadcopters with a set of virtual reality handles. control data is translated directly from VR to the real UAV in realtime. the experimental results showed a stable and convenient method of manipulation by the VR scene. With the support of the proposed system, ultra-remote control is possible, and immersive maneuvering makes controlling multiple drones easier.

关键词： Virtual reality

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Autonomous vision-Based Navigation and control for Intra-Row Weeding 18

Autonomous Vision-Based Navigation and Control for Intra-Row...

引用

IEEE 18th international conference on automation Science and Engineering (IEEE CASE)

作者： Aviles-Mejia, Jorge E. Soto, Daniel Stephant, Joanny Labbani-Igbida, Ouiddad Univ Limoges XLIM Res Inst UMR CNRS 7252 F-87032 Limoges France

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

For agriculture to become more sustainable, new practices and new cropping systems are needed to limit inputs such as fertilisers and phytosanitary products. this paper exposes an autonomous vision-based approach for navigation and intra-row weeding. To preserve crops (here concerned with maize and bean), a plant classification algorithm using easy-to-extract features has been developed and integrated on a real agricultural system. the approach uses frontal and proximal detection;the first allows for autonomous vision-based navigation without relying on GPS;and the latter regulates the weeding tool action. Realistic simulation scenarios are presented in order to validate the proposed approach as well as open-field experiments in real agricultural conditions obtained within the framework and evaluation campaigns of the ROSE challenge.

关键词： Visualization Navigation Plants (biology) Multimodal sensors Crops Real-time systems Classification algorithms

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Potential Hazard-Aware Adaptive Shared control for Human-Robot Cooperative Driving in Unstructured Environment 17

Potential Hazard-Aware Adaptive Shared Control for Human-Rob...

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17th international conference on control, automation, robotics and vision (ICARCV)

作者： Huang, Wenhui Zhou, Yanxin Li, Jianhuang Lv, Chen Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore

ISBN: (纸本)9781665476874

Research on the shared control system for humanin-the-loop cooperative driving has grown steadily in the past decade. However, most proposed methodologies were focused on structural roads such as highway rather than the unstructured environment. this paper presents a novel potential hazard-aware shared steering approach for human-robot cooperative driving in unstructured environment. First, we propose a hierarchical Gaussian risk field (HGRF) to evaluate the potential hazard of the predicted path. then an adaptive control authority allocation module is developed to engage the control in real-time. the control authority will be fully owned by the human driver when the vehicle drives in a safe manner. However, in the situation where the hazard level is predicted to be high, the authority of the human driver decrease, and the automation actively assists the driver by dynamically sharing the control authority to enhance safety and performance. the proposed methodology is experimentally verified with a steer-by-wire car-like mobile robot. the results show that our proposed approach can effectively engage and cooperatively control the vehicle in hazard cases, ensuring driving safety.

关键词： Shared control cooperative driving hazard evaluation control authority allocation

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Detection-segmentation convolutional neural network for autonomous vehicle perception 27

Detection-segmentation convolutional neural network for auto...

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27th international conference on Methods and Models in automation and robotics (MMAR)

作者： Baczmanski, Maciej Synoczek, Robert Wasala, Mateusz Kryjak, Tomasz AGH Univ Krakow Embedded Vis Syst Grp Dept Automat Control & Robot Krakow Poland

ISBN: (纸本)9798350311075

Object detection and segmentation are two core modules of an autonomous vehicle perception system. they should have high efficiency and low latency while reducing computational complexity. Currently, the most commonly used algorithms are based on deep neural networks, which guarantee high efficiency but require high-performance computing platforms. In the case of autonomous vehicles, i.e. cars, but also drones, it is necessary to use embedded platforms with limited computing power, which makes it difficult to meet the requirements described above. A reduction in the complexity of the network can be achieved by using an appropriate: architecture, representation (reduced numerical precision, quantisation, pruning), and computing platform. In this paper, we focus on the first factor the use of so-called detection-segmentation networks as a component of a perception system. We considered the task of segmenting the drivable area and road markings in combination with the detection of selected objects (pedestrians, traffic lights, and obstacles). We compared the performance of three different architectures described in the literature: MultiTask V3, HybridNets, and YOLOP. We conducted the experiments on a custom dataset consisting of approximately 500 images of the drivable area and lane markings, and 250 images of detected objects. Of the three methods analysed, MultiTask V3 proved to be the best, achieving 99% mAP(50) for detection, 97% MIoU for drivable area segmentation, and 91% MIoU for lane segmentation, as well as 124 fps on the RTX 3060 graphics card. this architecture is a good solution for embedded perception systems for autonomous vehicles. the code is available at: https://***/vision-agh/MMAR_2023.

关键词： detection-segmentation convolutional neural network autonomous vehicle embedded vision YOLOP Hybrid-Nets MultiTask V3

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Feature engineering techniques for skeleton-based two-person interaction classification in video 17

Feature engineering techniques for skeleton-based two-person...

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17th international conference on control, automation, robotics and vision (ICARCV)

作者： Puchala, Sebastian Kasprzak, Wlodzimierz Piwowarski, Pawel Warsaw Univ Technol Inst Control & Computat Engn Nowowiejska 15-19 PL-00665 Warsaw Poland

ISBN: (纸本)9781665476874

An LSTM-based approach to two-person interaction classification in image sequences, based on human skeleton detection in single frames, is proposed. the main contribution is the design of different preliminary feature extraction techniques from many skeleton data sets. the approach consists of four main stages. First, we employ the OpenPose engine in order to estimate silhouettes of persons in single video frames. Next, the skeleton data sets are tracked over time and particular joints are corrected whenever needed. then, three different versions of features are defined, based on the stream of refined skeleton joints. In the final stage, a classifier network, based on LSTM, is developed and experimentally studied. the models are trained and evaluated on the interaction subset of the NTU RGB+D data set. the most efficient model achieved a classification accuracy of 94.5% (in the CV mode). this is an excellent performance, comparable with the best reported Graph CNN-based classifiers for this subset.

关键词： Long short-term memory

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Data-driven Distributed MPC for Load Frequency control of Networked Nonlinear Power systems 17

Data-driven Distributed MPC for Load Frequency Control of Ne...

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17th international conference on control, automation, robotics and vision (ICARCV)

作者： Jia, Yubin Zhou, Jun Yong, Panxiao Guo, Jun Southeast Univ Sch Automat Nanjing 210096 Jiangsu Peoples R China Southeast Univ Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing 210096 Peoples R China

ISBN: (纸本)9781665476874

In this paper we proposed a data-driven distributed model predictive control (MPC) for the load frequency control of the multi-area interconnection nonlinear power system. the data-driven Koopman operator method is used to deal with the nonlinear wind power generation system in each area. the distributed Koopman operator algorithm is proposed to deal with the huge amount of data in the large-scale distributed system. Based on the distributed linear model obtained by the distributed Koopman operator algorithm, the distributed MPC is applied to realize the load frequency control (LFC) of the multi-area power system. the cooperation-based cost function is optimized by the MPC controller in each area, and the global optimal solution can be achieved by the proposed method. the effectiveness and practicability of the proposed algorithm are demonstrated by the simulation.

关键词： Model predictive control

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Particle swarm optimization-based method of source seeking by small robotic groups in the presence of noises and communication constraints 9

Particle swarm optimization-based method of source seeking b...

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9th international conference on robotics and automation Engineering, ICRAE 2024

作者： Makarov, Nikolai Matveev, Alexey Gusev, Sergei Sirius University Mathematical Robotics Science Division Sirius Federal Territory Russia

ISBN: (纸本)9798331518301

the paper deals with the problem of cooperatively finding a source of an unknown environmental field by a relatively small group of robots whose communication range is finite. To solve this problem, a distributed control law is proposed, which is based on the ideas of the particle swarm optimization techniques. To disclose the impacts of the number of agents, their communication radii, and the noise level on the performance of the algorithm, intensive Monte Carlo simulation studies are performed, with a particular attention to relatively small groups. Comparative analysis of two opposite strategies of the robots' initial placement on the perimeter of the zone of search is also performed. the first of them comes to disembarkment of the robots in a tight cluster at the start of the mission, the second one consists in their uniform distribution over the perimeter. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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(r, Q) Inventory control in Multi-Modal Distribution Systems with Flexible Channel Allocation 17

(r, Q) Inventory Control in Multi-Modal Distribution Systems...

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17th international conference on control, automation, robotics and vision (ICARCV)

作者： Ignaciuk, Przemyslaw Lodz Univ Technol Inst Informat Technol Lodz Poland

ISBN: (纸本)9781665476874

In order to improve supply system robustness, or gain cost advantage, multiple delivery modes may be used. In this work, the (r, Q) inventory policy is formally investigated as a tool to control the resupply process of a remote depot that answers uncertain market demand. In the considered scenario, the goods are relocated using multiple channels with diverse properties concerning transportation delay, lot size, and quality, e.g., trucks, or trains. the lot partitioning strategy is adapted on the fly to the current channel characteristics. A dynamic model of the supplier-depot interaction is built and used to evaluate the policy properties in a robust control framework. Using the constructed framework, it is explicitly shown how to select the policy parameters to obtain full demand realization, thus eliminating backorders, irrespective of the pattern of delay and demand fluctuations. It is also discussed how to assign the warehouse space at the depot so that emergency storage will not be required even though, as a result of channel disruptions, deliveries from a few periods arrive simultaneously, or out of order.

关键词： Inventory control multi-modal transport dynamic scheduling

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Stochastic Stability and L1-gain control of Positive Markov Switching Systems with Impulses 17

Stochastic Stability and L1-gain Control of Positive Markov ...

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17th international conference on control, automation, robotics and vision (ICARCV)

作者： Hu, Meng-Jie Park, Ju H. China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221000 Jiangsu Peoples R China Yeungnam Univ Dept Elect Engn Gyongsan 38541 South Korea

ISBN: (纸本)9781665476874

this paper studies the stability and L-1-gain control of positive systems with Markov switching parameters and impulses. Markov process is applied to describe the switching parameters and structures. the positivity constraint, Markov stochastic processes and impulsive jumps are taken into account in a unified framework. By utilizing the stochastic co-positive Lyapunuov function, some new conditions on stochastic stability and L-1-gain characterization of positive impulsive Markov switching systems (PIMSSs) are acquired. the stochastic stability and L-1-gain characterization of the closed-loop systems can be ensured via the L-1-gain mode-dependent state-feedback controller. Moreover, an example is presented to exhibit the usefulness of the obtained results.

关键词： Stochastic systems

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