Current Issue : October-December Volume : 2024 Issue Number : 4 Articles : 5 Articles
In order to solve the problem whereby the original DWA algorithm cannot balance safety and velocity due to fixed parameters in complex environments with many obstacles, an improved dynamic window approach (DWA) of local obstacle avoidance for robots is proposed. Firstly, to assure the path selection stationarity and enhance the navigation ability of inspection robot, the velocity cost function of the original DWA was improved and the distance cost function of the target point was added. Then, the distances among the inspection robot, observed obstacles, and target points were input into a fuzzy control module, and the fuzzy weights of the velocity and distance cost functions were obtained, by which the motion of the inspection robot can continuously self-adjust and adapt to the unknown environment. Finally, several simulations and experiments were conducted. The results show that the improved DWA algorithm can effectively improve the obstacle avoidance ability of inspection robots in complex environments. The path can be more reasonably selected and the safety of inspection robots can be enhanced, while the safe distance, path length, and the number of samples can also be optimized by the improved DWA compared to the original DWA....
Aiming to solve the problem that the significant error between the actual joint torque and the calculated joint torque of a welding robot leads to the vibration of the end-effector, which in turn affects the stability of the end-effector, this paper proposes a identification algorithm based on the Weighted Least Squares Genetic Algorithm (WLS-GA) to construct and solve the dynamical model to obtain the accurate dynamical parameters. Firstly, a linear model of welding robot dynamics is derived. The fifth-order optimal Fourier series excitation trajectory is designed to collect experimental data such as joint torque. Then, a rough solution of the parameters to be recognized is obtained by solving the dynamics model through the Weighted Least Squares (WLS) method, the search space is determined based on the rough solution, and the optimal solution is obtained by using the Genetic Algorithm (GA) to perform a quadratic search in the search space. Finally, the identification data obtained from the algorithm is analyzed and compared with the experimental data. The results show that the error between the identification data obtained using the WLS-GA identification algorithm and the experimental data is relatively small. The results show that the identification data obtained using the WLS-GA identification algorithm have less error than the experimental data, taking the Root Mean Square (RMS) value of the joint torque error obtained using the weighted least squares algorithm as a criterion. The accuracy of the WLS-GA identification algorithm can be improved by up to 66.85% compared with that of the weighted least squares algorithm and by up to 78.0% compared with that of the Ordinary Least Squares (OLS) algorithm. In summary, the WLS-GA identification algorithm can accurately identify the dynamic parameters of the welding robot and more accurately construct a dynamic model to solve the effect of joint torque error on the control characteristics of the welding robot. It can improve the stability of the end-effector of the welding robot to ensure the quality of the automobile body and beam welding and welding speed....
Due to the exponential growth of cars in urban areas, parking problems have become a significant concern. Addressing this issue requires efficient methods for locating available parking spaces, enhancing the overall experience for drivers. This paper introduces a parking lot recommendation model leveraging meta-heuristic algorithms to generate a list of potential parking locations based on the user’s travel destinations. The primary objectives of these algorithms include minimizing travel distance, reducing total parking fees, and selecting parking lots with ample available spaces. The proposed model incorporates bio-inspired algorithms, including simulated annealing, genetic algorithms, and their adaptive variants. Our evaluation compares the performance of these algorithms, highlighting the adaptive simulated annealing’s superior quality of solutions and robustness against local minima. However, it is important to note that this approach comes with a trade-off, requiring longer execution times. In summary, this research contributes a novel parking lot recommendation model that effectively addresses the challenges posed by urban parking. The performance evaluation underscores the efficacy of the adaptive simulated annealing approach, showcasing its potential for practical implementation despite its relatively longer execution time....
Unmanned Aerial Vehicle (UAV) infrared detection has problems such as weak and small targets, complex backgrounds, and poor real-time detection performance. It is difficult for general target detection algorithms to achieve the requirements of a high detection rate, low missed detection rate, and high real-time performance. In order to solve these problems, this paper proposes an improved small target detection method based on Picodet. First, to address the problem of poor real-time performance, an improved lightweight LCNet network was introduced as the backbone network for feature extraction. Secondly, in order to solve the problems of high false detection rate and missed detection rate due to weak targets, the Squeeze-and-Excitation module was added and the feature pyramid structure was improved. Experimental results obtained on the HIT-UAV public dataset show that the improved detection model’s real-time frame rate increased by 31 fps and the average accuracy (MAP) increased by 7%, which proves the effectiveness of this method for UAV infrared small target detection....
Linear regression is one of the most widely used predictive models in statistics and machine learning. This paper aims to comprehensively discuss the theoretical basis, mathematical principle and application of linear regression algorithm in various fields. Firstly, this paper introduces the research background and significance of linear regression, and summarizes its important role in modern data analysis. Then, the paper elaborates the basic theory of linear regression, including its definition, assumptions, parameter estimation methods and model diagnosis and selection. In addition, different types of linear regression are classified and discussed, such as simple linear regression, multiple linear regression and logistic regression, and the specific application scenarios of each type are analyzed....
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