This paper uses a method based on the YOLOv5s network to study the real-time traffic light detection task in the vehicle-mounted intelligent system. Due to the limitation of computing resources on the actual vehicle a...
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In this study, we propose a reinforcement learning (RL) based position control method for a one-degree-of-freedom (1-DOF) rotational hydraulic actuator. controlling hydraulic actuators is challenging due to their nonl...
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ISBN:
(纸本)9798331517939;9788993215380
In this study, we propose a reinforcement learning (RL) based position control method for a one-degree-of-freedom (1-DOF) rotational hydraulic actuator. controlling hydraulic actuators is challenging due to their nonlinear characteristics and complex structure. Reinforcement learning offers the advantage of enabling control through learning without requiring a detailed understanding of the model, using virtual environments. However, simulators do not perfectly replicate real-world conditions. To address this, we aim to enhance the fidelity of the simulation and improve the performance of reinforcement learning-based controllers by integrating real-world data into the simulation using deep neural networks (DNN). The reinforcement learning is trained using the Proximal Policy Optimization (PPO) algorithm, and it is validated through experiments with step and sine inputs.
Central Pattern Generators (CPG) nonlinear oscillation network is being increasingly used in the control of multi-joint collaborative robots. The motion attitude of robots can be effectively adjusted by tuning paramet...
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ISBN:
(纸本)9798350377712;9798350377705
Central Pattern Generators (CPG) nonlinear oscillation network is being increasingly used in the control of multi-joint collaborative robots. The motion attitude of robots can be effectively adjusted by tuning parameters of the CPG neural network. However, the mapping from CPG parameters to motion attitude is relatively complicated. To improve the motion performance, an optimization method combining computational fluid dynamics (CFD) and CPG network is proposed. In this work, we design a three-joint biomimetic soft robot fish following the body structure of trevally and an improved CPG network based on the Hopf model is incorporated into the control system. Directly optimizing the swimming performance through experiments is time consuming and complex, a mode of first adjusting parameters on the simulation platform and then refining on the robot is usually adopted. Therefore, a CFD simulation platform using hydrodynamic solutions has been established to assist in analyzing the swimming effect. Finally, the experimental results show that the swimming simulation by the CFD is highly similar to the real test, and the swimming performance after the improved CPG network optimization has been significantly increased.
Based on the intelligent translation hardware system, this article discusses the existing situation of the Japanese explanation of the 5A-level scenic spots in Jiangxi Province from the perspective of the Japanese exp...
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Numerous graduates complete their undergraduate / postgraduate degrees each year, following various paths. A college's alumni should be kept in contact in order to help students connect with more opportunities and...
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Music learning plays an important role in cultivating the aesthetic taste and developing creativity of young people. The current traditional music education is unable to provide rich and diverse learning resources, no...
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This research proposes a method for traversability analysis and path planning using obstacle recognition information in a multi-robot system. To avoid collisions and optimize paths in environments with multiple robots...
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ISBN:
(纸本)9798331517939;9788993215380
This research proposes a method for traversability analysis and path planning using obstacle recognition information in a multi-robot system. To avoid collisions and optimize paths in environments with multiple robots, we present a method where robots share obstacle information and plan their paths accordingly. Obstacle information detected by each robot is monitored by a central server, which uses this information to dynamically replan the path. Experimental results show that sharing obstacle information enables robots to consider out-of-view obstacles, reducing collision risks and enhancing system efficiency compared to non-collaborative systems. This research demonstrates the feasibility of flexible path replanning based on obstacle information for the efficient operation of multiple robots.
Vision-assisted container loading of Rubber Tyred Gantry (RTG) cranes are facing two primary challenges. Firstly, the uncertainty inherent in Covolutional Neural Network (CNN) based detection hinders its direct applic...
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ISBN:
(纸本)9798350377712;9798350377705
Vision-assisted container loading of Rubber Tyred Gantry (RTG) cranes are facing two primary challenges. Firstly, the uncertainty inherent in Covolutional Neural Network (CNN) based detection hinders its direct application in the safety-critical operation of such heavy-duty machinery. Secondly, sensor calibration introduces additional complexities and errors into the system. However, existing studies have not adequately addressed these challenges. Motivated by this gap, this paper proposes an integrated approach for target detection and alignment control in container loading of RTG cranes. To ensure reliable target marker identification, a heuristic post-processing algorithm is developed as a complement to CNN-based foreground segmentation, thereby ensuring safety during the container handling process. On this basis, a pixel-based control scheme is designed to align the container with the target markers, which eliminates the need for offline or online sensor calibrations. The proposed approach has been successfully implemented on a real RTG crane manufactured by Shanghai Zhenhua Heavy Industries Co., Ltd. (ZPMC) and validated at the Port of Ningbo, China. Experimental results demonstrate the superiority of the proposed approach over current manual operations in port industries, highlighting its potential for crane automation.
Mining at the problems of short range and incomplete charging facilities of electric vehicles, a sunshade device and intelligentcontrol system for electric vehicles have been designed. This device can charge electric...
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ISBN:
(纸本)9798350351040;9798350351033
Mining at the problems of short range and incomplete charging facilities of electric vehicles, a sunshade device and intelligentcontrol system for electric vehicles have been designed. This device can charge electric vehicles when they are parked outdoors and has efficient photovoltaic power generation, which can meet the urgent needs of charging while also providing insulation and shading. This device collects and analyzes data in real-time through various sensors and intelligentcontrolsystems, achieving automatic and safe deployment of solar panels on the root In addition, the lower layer of the panel adopts thermal radiation coating materials to enhance the sun shading and thermal insulation effect, achieving an integrated energy harvesting and sun shading device.
From the Turing Machine in the late 1930s which was hypothesized to be capable of simulating any algorithmic computation to modern computers that can execute intricate computations, the progress in computing has been ...
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