This paper showcases a real-world example of a system that achieves collaborative localization and mapping of multiple agents within a building. The proposed system processes the odometry and 3D point cloud data colle...
This paper showcases a real-world example of a system that achieves collaborative localization and mapping of multiple agents within a building. The proposed system processes the odometry and 3D point cloud data collected by the agents moving around the building to automatically generate the building’s floorplan on which the agent trajectories are overlaid. The wearable hardware consists of a low-cost passive integrated sensor that includes both a camera and an IMU (Inertial Measurement Unit) and an embedded compute unit. The system’s capabilities are shown through real-world experiments.
We study the problem of regret minimization in a multi-armed bandit setup where the agent is allowed to play multiple arms at each round by spreading the resources usually allocated to only one arm. At each iteration ...
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The Koopman operator framework allows to embed a nonlinear system into a linear one. This enables the analysis, estimation, and control of nonlinear dynamics with linear methods. controllers based on the Koopman opera...
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The Koopman operator framework allows to embed a nonlinear system into a linear one. This enables the analysis, estimation, and control of nonlinear dynamics with linear methods. controllers based on the Koopman operator (KO) are often model predictive control (MPC) schemes. The performance of an MPC depends on the prediction accuracy of its model. Hence, it is meaningful to update the model online if the predictions are not sufficiently accurate. In this work, we approach this problem by using a recursive least squares (RLS) algorithm with forgetting factor. Furthermore, we show in an empirical case study that combining the KO with an online update and the recently proposed quasi-linear parameter-varying model predictive control (qLMPC) algorithm results in an efficient control scheme.
Aiming at a large number of ambiguous,imprecise and incomplete data in the real world,fuzzy time series has come into being and developed into an effective forecasting *** the process of modeling and forecasting of fu...
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Aiming at a large number of ambiguous,imprecise and incomplete data in the real world,fuzzy time series has come into being and developed into an effective forecasting *** the process of modeling and forecasting of fuzzy time series,the prediction performance of fuzzy time series can be effectively improved by partitioning the universe of discourse into different *** this paper,a forecasting approach for fuzzy time series,which introduces the granularity mechanism into interval division and employs differential data for incremental forecasting,is proposed to solve the problem of time series forecasting with high forecasting *** the proposed approach,in order to describe the fuzzy logic relationship and fuzzy trend of historical data,we first do differential processing on the historical ***,Fuzzy C-means(FCM) clustering algorithm is used to generate several partition intervals *** the sequel,we use the principle of justifiable granularity to constantly adjust the width of all the intervals,so that these information granules associated with corresponding intervals become the most"informative" information ***,the boundary of information granules is used as the basis of interval division to complete the forecasting *** illustrative example is provided to demonstrate the essence of the proposed *** comparative experiment with other representative approaches shows that the proposed approach can significantly improve the prediction accuracy of time series.
Aiming at the problem of how to realize the reasonable distribution of goods and the resource scheduling of route planning under dynamic conditions, a phased refresh method is proposed to deal with the requirements in...
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Aiming at the problem of how to realize the reasonable distribution of goods and the resource scheduling of route planning under dynamic conditions, a phased refresh method is proposed to deal with the requirements in sections. At the same time, the clustering method is introduced to generate the initial population. And the cross and mutation rate is determined by a step-by-step reduction method, which is used to solve the problem of the traditional genetic algorithm falling into the local optimum caused by the uneven distribution of searchable solutions. Finally, the effectiveness of the improved method is verified by simulation experiments.
This paper investigates the high-precision path tracking control of tracked paver combined with global satellite navigation *** the paver is performing paving operations,it requires high path tracking accuracy and goo...
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This paper investigates the high-precision path tracking control of tracked paver combined with global satellite navigation *** the paver is performing paving operations,it requires high path tracking accuracy and good vehicle ***,considering the influence of road curvature on path tracking accuracy and vehicle stability,and the situation that the vehicle can not move quickly to the expectation path when the lateral position of the vehicle deviates from the expectation path,this paper proposes a lateral path tracking control method based on improved Pure Pursuit *** control method is verified through *** experimental results show that the maximum lateral tracking error of the improved algorithm is 0.04 m,which is 55.56% lower than that of the original algorithm,and the average lateral tracking error is 0.02 m,which is60% lower than that of the original *** purpose of high-precision path tracking of the paver is realized.
Adaptive control architectures often make use of Lyapunov functions to design adaptive laws. We are specifically interested in adaptive control methods, such as the well-known L1 adaptive architecture, which employ a ...
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作者：
Ghoul, YamnaNaifar, OmarUniversity of Tunis El Manar
National Engineering School of Tunis LR11ES20 Analysis Conception and Control of Systems Laboratory BP 37 Le Belvédère 1002 Tunis Tunisia University of Sfax
National Engineering School of Sfax Control and Energy Manamgment laboratory Tunisia University of Kairouan
Higher Institute of Applied Sciences and Technology Kairouan Tunisia
The home automation system is becoming increasingly popular due to its many benefits, which involve remotely monitoring and controlling household appliances. As the internet and its applications continue to grow, ther...
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The home automation system is becoming increasingly popular due to its many benefits, which involve remotely monitoring and controlling household appliances. As the internet and its applications continue to grow, there is enormous potential for remotely accessing and controlling and monitoring network-enabled devices. This article examines various smart home systems and automation technologies from different functional angles. The article focuses on the home automation concept, which uses smart devices to accelerate control and monitoring operations. The article also provides a review of versatile home systems and automation technologies, which can be controller-based (using Arduino or Raspberry pi), cloud-based, Bluetooth-based, SMS-based, ZigBee-based, mobile-based, RF module-based, web-based, and internet-based. The objective of this project is to create a home automation application using IoT technology. The system proposed includes multiple sensors that gather temperature and humidity data, which is then processed using an Arduino and Raspberry microcontroller that are connected to an Android mobile application. The data is transmitted to the mobile app via Zigbee protocol and updated in real-time. To measure temperature and humidity, a DHT11 sensor is utilized. To monitor gas leaks in the kitchen, an MQ2 sensor is incorporated. Lastly, a HC-SR04 Ultrasonic sensor is utilized to manage the garage door's opening and closing. The proposed system involves testing the air conditioning by using the DHT11 sensor to monitor the humidity and temperature of our smart home, along with a fan as an actuator in case of an increase in temperature or a decrease in humidity. For the home automation application, the Xbee module (of the Zigbee protocol) was chosen, which can be configured as a coordinator, router, or even an endpoint. However, we need to communicate between two cards, one as the master and the other as the application, so we will start by configuring the modules
In the modern manufacturing environment, the production systems develop towards a flexible direction due to the market demands of multiple varieties and small batch-based customized products. To make better use of the...
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In the modern manufacturing environment, the production systems develop towards a flexible direction due to the market demands of multiple varieties and small batch-based customized products. To make better use of the existing resources and to improve production efficiency, distributed manufacturing mode begins to appear. This paper concentrates on a multi-type production scheduling problem for distributed serial lines. Specifically, unreliable machines and finite buffers are considered,which are more realistic in the practical production. The mathematical model for the production system with two Bernoulli machines is formulated first. Then, under the hypothetical model mentioned above, the main work of this article is to propose the exact and approximate analyses to calculate the performance indicators. Based on the analysis of the model, the genetic algorithm is applied to optimize the maximum completion time on the distributed serial lines for multi-batch-based production tasks. Finally, the feasibility and effectiveness of the mathematical model and the proposed algorithm are verified through numerical experiments.
The deep crate grasping problem is a major challenge for manipulator in industrial applications. In order to solve the issue of deep crate grasping and ensure the path quality of the algorithm, this paper proposes a n...
The deep crate grasping problem is a major challenge for manipulator in industrial applications. In order to solve the issue of deep crate grasping and ensure the path quality of the algorithm, this paper proposes a new hybrid obstacle avoidance planning algorithm based on goal-biased rapidly exploring random tree and improved artificial potential field (RRT-APF). Initially, the algorithm strategizes an efficient trajectory for the working element within the operational area. Subsequently, it dissects this trajectory through sampling, creating a sequence of sub-target points. These points serve as the basis for obstacle avoidance planning within the manipulator's configuration space, mitigating planning complexities. Moreover, the RRT algorithm is employed to address the challenge of local optima within the artificial potential field method. The stochastic nature of the RRT algorithm plays a crucial role in enabling the APF algorithm to break free from local optima. Ultimately, the efficacy of the algorithm is demonstrated through the planning of a path for obstacle avoidance on the DOBOT CR5 manipulator using MATLAB.
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