In this paper, a method of calculating the occupancy of a shelf will be presented. A vision pillar composed of two RGB cameras and two ToF depth cameras will be used to scan a shelf and determine the percentage of emp...
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This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They h...
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In the paper, the authors check the behaviour of Bluetooth Low Energy protocol in a popular smart wristband and a microcontroller in the heart rate monitoring application. The measurements were collected using a devel...
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In the paper, the authors check the behaviour of Bluetooth Low Energy protocol in a popular smart wristband and a microcontroller in the heart rate monitoring application. The measurements were collected using a development board with the ESP32 System on Chip. The authors tested measurement period stability and measurement reliability in various conditions.
Application of learning to collaborative tracking control of multi-agent systems has addressed a wealth of problems across transportation, manufacturing, rescue, aerospace and medical care areas. Iterative learning co...
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
Application of learning to collaborative tracking control of multi-agent systems has addressed a wealth of problems across transportation, manufacturing, rescue, aerospace and medical care areas. Iterative learning control algorithms have been proposed to address synergistic objectives in general optimization problems, achieving a transparent balance between convergence speed, tracking error and robustness. This paper builds on this framework by formulating a point-to-point strategy that allows each subsystem to track only a portion of the trajectory, thereby providing a more flexible design framework with broad utility. Moreover, a channel tracking strategy is developed to ensure that the total output during untracked intervals is limited to an a specified range. The practicality of this novel control framework is illustrated through derivation, simulation and evaluation of three new iterative learning laws: inverse, gradient and norm-optimal. Convergence analysis for the proposed framework is also given.
Takeaway delivery has become an important part of urban life. However, terminal deliveries are often blocked by security measures that often prevent them from arriving on time. Designing a takeaway delivery robot can ...
ISBN:
(数字)9781837242672
Takeaway delivery has become an important part of urban life. However, terminal deliveries are often blocked by security measures that often prevent them from arriving on time. Designing a takeaway delivery robot can solve this problem to a large extent. In this paper, path planning algorithm level of designing a takeaway robot is researched. In this paper, the research is carried out by closely focusing on the current stage of the path planning algorithm related difficulties. Three typical algorithms are selected for simulation testing within the scope of graph search algorithms. These three algorithms are Dijkstra algorithm, A* algorithm and rapidly-exploring random tree (RRT) algorithm. The final comparison is made with the simulation test results. And to find the optimal path planning algorithm for takeaway delivery robots within the range of graph search algorithms. This paper provides a reference for the path planning algorithm level of takeaway delivery robot design. At the same time, it helps to improve the delivery service of takeaway terminal.
Sarcasm detection has established itself as one of the more difficult Natural Language Processing tasks, due to the complex nature of sarcasm. This paper aims to benchmark the performance of state-of-the-art models li...
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In this paper, we consider the synchronization of heterogeneous pulse-coupled oscillators (PCOs), where some of the oscillators might be faulty or malicious. The oscillators interact through identical pulses at discre...
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This work addresses the challenge of vehicle mass estimation using a longitudinal vehicle dynamics model, which adopts an errors-in-variables formulation due to the presence of noise-contaminated measurements in both ...
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This work addresses the challenge of vehicle mass estimation using a longitudinal vehicle dynamics model, which adopts an errors-in-variables formulation due to the presence of noise-contaminated measurements in both input and output variables. The reduced vehicle dynamics model is ill-conditioned by nature of correlated input variables and a lack of persistent excitation in the measured data. A regularized iterative weighted total least squares (RIWTLS) method is therefore developed and has the advantage of producing parameter uncertainty quantification and measurement bias estimation alongside the estimated system parameters. A complementary adaptive regularization scheme is developed and serves to control the numerical stability of the RIWTLS algorithm based on the conditioning of incoming data. Experimental tests using electric vehicle data and a batch estimation scheme highlight the performance of the proposed RIWTLS algorithm, estimating vehicle mass to within ±1% accuracy.
This review aims to contribute to the quest for artificial general intelligence by examining neuroscience and cognitive psychology methods for potential inspiration. Despite the impressive advancements achieved by dee...
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Database technology applies to many engineering problems. Hence it is the subject of study at many university majors. Since teaching practical usage of theory at a distance is difficult or even impossible, we present ...
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