With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operatin...
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With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operating traffic *** study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning *** fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal ***,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition *** second aspect involves predicting traffic volume using the long short-term memory ***,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent ***,the fusion of the obtained results leads to a final traffic volume *** experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and *** achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the *** findings highlight the accuracy of traffic pattern ***,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.
To address the global challenge of population aging, our goal is to enhance successful aging through the introduction of robots capable of assisting in daily physical activities and promoting light exercises, which wo...
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The implementation of a patient monitoring system and infusion automation which aims to ensure regular and periodic monitoring of inpatient conditions are applied in this system. This embedded system is applied in hos...
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This paper presents an original detection system for measuring the speed of vehicles on a road used in the laboratory for educational and testing purposes. Although the maximum speed limit is specified for each type o...
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Accurate identification of the subthalamic nucleus (STN) borders is time-consuming, relying heavily on the neurosurgeon expertise in manually interpreting the electrophysiological signals. Local field potentials (LFPs...
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Visual impairment affects the ability to navigate independently in an unknown environment due to reliance on human/dog assistance, potential miscommunication, and discomfort during mobility. To make the visually impai...
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Recent research on quadruped robots has been achieving high-performance motion control based on optimization and reinforcement learning (RL). However, there is still ongoing research aimed at demonstrating that implem...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Recent research on quadruped robots has been achieving high-performance motion control based on optimization and reinforcement learning (RL). However, there is still ongoing research aimed at demonstrating that implementing high-performance motion based on simple and dominant dynamic principles is possible. In this paper, we proposed a novel control approach that projects Spring-Loaded Inverted Pendulum (SLIP) dynamics to articulated legs, utilizing admittance control based force observer within a rotating workspace (RWFOB). Unlike other legged robots that depend on sensor-based estimation of external forces, the proposed method presents an alternative approach that reduces the reliance on sensors. Additionally, we introduce a comprehensive control framework for quadruped robot motion control, establishing the connection between trunk and SLIP-realized leg movements using Jacobian. Through comparative analysis with Virtual Model Control (VMC) in simulations, we illustrate the effectiveness of the proposed framework as a robust and reliable trunk feedback controller.
Background: This study investigates gait dynamic stability on inclined surfaces while walking with foot rotational impairments such as everted and inverted feet. Walking stability is assessed during gait transitional ...
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Background: This study investigates gait dynamic stability on inclined surfaces while walking with foot rotational impairments such as everted and inverted feet. Walking stability is assessed during gait transitional periods i.e. weight loading and unloading phases. Methods: Foot rotational impairments (eversion and inversion) are imitated using wedged foot insoles. A total of ten healthy subjects performed five trials for each of the inverted, everted, and normal feet conditions. Experimental data was collected using a twelve-camera motion capture system and a force plate installed on an inclined platform. Lower limb joint kinematics were computed in Visual-3D motion analysis software to evaluate the degree of foot rotational impairments. Gait dynamic stability was assessed by analysing the centre of mass and centre of pressure signals as neuromechanical input and output responses respectively. Both signals were modelled in time and frequency domains and stability margins were quantified by applying Nyquist and Bode (N&B) methods from control engineering theory. Results: Stability margins quantified from N&B methods illustrated the loading phase as stable and the unloading phase as unstable gait transitions. During the loading phase, both rotational impairments illustrated a decrease in stability (p < 0,05) for the ramp ascent walk and an increase in stability (p < 0,05) for the ramp descent walk. However, there was no difference observed for the respective unloading phases. Results from neuromotor outputs (CoP-velocity) illustrated a strong interlimb correlation (p < 0,001) during gait transitional periods, implying a compensatory stability interaction exists between opposite limbs. Further, stabilities quantified from outputs were found greater in magnitudes than the instability quantified from inputs illustrating the robustness of neuromotor balance control. Conclusions: Results support the hypothesis that gait stability gets affected while walking with rotation
This paper introduces a novel method for identifying the inertia matrix of multi-DOF Flexible Joint Robots (FJR) that is robust to nonlinearity. By leveraging resonance and anti-resonance frequencies in the Frequency ...
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ISBN:
(数字)9798350394085
ISBN:
(纸本)9798350394092
This paper introduces a novel method for identifying the inertia matrix of multi-DOF Flexible Joint Robots (FJR) that is robust to nonlinearity. By leveraging resonance and anti-resonance frequencies in the Frequency Response Functions (FRF), our approach overcomes limitations of conventional methods prone to mechanical nonlinearities, offering more accurate robot control. Additionally, it highlights the benefits of frequency domain system identification, including nonlinear robustness and flexible joint decomposition into motor and load components. A novel sequential excitation algorithm is proposed for inertia matrix determination, validated through simulation and experiment.
Recent research on quadruped robots has been achieving high-performance motion control based on optimization and reinforcement learning. However, there is still ongoing research aimed at demonstrating high-performance...
详细信息
ISBN:
(数字)9798350394085
ISBN:
(纸本)9798350394092
Recent research on quadruped robots has been achieving high-performance motion control based on optimization and reinforcement learning. However, there is still ongoing research aimed at demonstrating high-performance motion based on simple and dominant dynamic principles. In this paper, we proposed a novel control approach that projects Spring-Loaded Inverted Pendulum (SLIP) dynamics to articulated legs, utilizing admittance control based force observer within a rotating workspace (RWFOB). Unlike other legged robots that depend on sensor-based estimation of external forces, the proposed method presents an alternative approach that reduces the reliance on sensors. Additionally, we introduce a comprehensive control framework for quadruped robot motion control, establishing the connection between trunk and SLIP-realized leg movements using Jacobian. The effectiveness of the proposed framework as a robust and reliable trunk feedback controller is validated through simulation and experiments.
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