Traffic congestion has become a major issue that is being faced by the majority of road users. The increasing vehicle usage, and the lack of space and funds to construct new transport infrastructure, further complicat...
详细信息
Compared with separate solar or wind generation, the hybrid wind-solar-hydro renewable portfolio can achieve better generation characteristics due to their temporal-spatial complementarities. This paper proposes optim...
详细信息
Water quality monitoring is necessary for enabling qualified water reuse, which has been gaining acceptance as a method of water supply augmentation. ICT solution can facilitate water treatment and monitoring (WTM) by...
详细信息
This paper presents a CMOS-based neuromorphic circuit that can simulate self-oscillatory firing behaviors. Based on the leaky integrate-and-fire neuron model, a dynamic bias controller and an excitation integrator are...
详细信息
Physical human-robot collaboration requires strict safety guarantees, due to the fact that robots and humans work in a shared workspace. This paper presents a novel control framework to handle safety-critical position...
详细信息
Physical human-robot collaboration requires strict safety guarantees, due to the fact that robots and humans work in a shared workspace. This paper presents a novel control framework to handle safety-critical position-based constraints for human-robot physical interaction. The proposed methodology is based on admittance control, exponential control barrier functions (ECBFs), and quadratic program (QP) to achieve compliance during the force interaction between human and robot, while simultaneously guaranteeing safety constraints. In particular, the formulation of admittance control is formulated as a second-order nonlinear control system, and the interaction forces between humans and robots are regarded as the control input. A virtual force feedback for admittance control is provided in real-time by using the ECBFs-QP framework as a compensator of the external human forces. A safe trajectory is therefore derived from the proposed adaptive admittance control scheme for a low-level controller to track. The main innovation of the proposed approach is the ability to enable the robot to naturally comply with human forces without violating any safety constraints, even when external human forces incidentally force the robot to do so. The effectiveness of our approach is demonstrated in simulation studies on a two-link planar robot manipulator.
Spatial frequency (SF) is a characteristic of an image that could dissociate course and fine shape information. Physiological and psychophysical studies widely investigated the role of various SF contents in image pro...
详细信息
Spatial frequency (SF) is a characteristic of an image that could dissociate course and fine shape information. Physiological and psychophysical studies widely investigated the role of various SF contents in image processing. Inspired by the primate brain structure, deep neural networks improved various computer vision tasks such as image classification. Physiological studies show that low SF (LSF) contents of an image could be processed faster to provide feedback to facilitate object recognition. However, this knowledge has not been considered in designing neural network structures. This study introduces SFNet, a new neural network structure that employs an LSF-based feedback mechanism. SFNet is a two-stream structure where one stream is used for LSF processing to provide feedback for image classification. The other stream combines the LSF-based feedback and the HSF processing to form the final decision. The role of the proposed LSF-based feedback in image classification is investigated utilizing the CIFAR100 dataset. The results show that SFNet improves the performance in the presence of SF filtering compared to the equivalent structures.
Unmanned Aerial Vehicles (UAVs), particularly quadcopters, have found growing applications across diverse sectors such as surveillance, precision agriculture, and transport. However, their nonlinear dynamics, underact...
详细信息
This paper presents the application of Fractional Order Sliding Mode control (FO-SMC) in order to achieve a robust motion trajectory regulation in dynamic robot systems. The proposed control strategy benefits of both ...
详细信息
ISBN:
(数字)9798350378382
ISBN:
(纸本)9798350378399
This paper presents the application of Fractional Order Sliding Mode control (FO-SMC) in order to achieve a robust motion trajectory regulation in dynamic robot systems. The proposed control strategy benefits of both advantages of fractional calculus and sliding mode control to upgrade the robustness and the performances of the controller. Moreover, the paper proposes to use a fuzzy tuning of sliding mode controller in order to satisfy the capabilities of the actuators. The stability of the closed loop system has been demonstrated using the Lyapunov theory. Simulation results demonstrate the efficiency of the proposed method achieving precise trajectory tracking and robust performances, it has been shown that fuzzy tuning of the sliding function parameters significantly reduces control variable peaks, making the control more suitable for actuator application.
Aiming at the ore blending problem in the open-pit mining scenario, the optimization objective is to minimize the grade variance of the sliding window of the ore flow, and a cooperative shovel scheduling model for rea...
详细信息
ISBN:
(数字)9798350368604
ISBN:
(纸本)9798350368611
Aiming at the ore blending problem in the open-pit mining scenario, the optimization objective is to minimize the grade variance of the sliding window of the ore flow, and a cooperative shovel scheduling model for real-time ore blending is established. A reinforcement learning-enhanced dynamic multi- objective evolutionary algorithm is proposed, where a Q-learning operator selection mechanism is introduced to reuse the information from the previous environment for tracking the optimal solution in the dynamic environment. Experimental results show that the proposed method can effectively control the grade fluctuation of the ore flow and dynamically respond to external events, and can find a better solution in real time compared with the traditional operator selection algorithm.
This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the ...
详细信息
暂无评论