Object detection in surveillance videos is challenging task whenever the objects are similar to other objects and overlapped with each *** objects may be masked or cover with any transparent or non transparent *** to ...
详细信息
The proceedings contain 60 papers. The topics discussed include: military actions and climate change as drivers of wildfires in northern regions of Ukraine in 2022-2023;investigation of regeneration and spreading of b...
The proceedings contain 60 papers. The topics discussed include: military actions and climate change as drivers of wildfires in northern regions of Ukraine in 2022-2023;investigation of regeneration and spreading of black locust (Robinia pseudoacacia L.) in Lithuania;analysis of possibilities for rainwater harvesting from green roofs as a part of sustainable water management in Lithuania;enhancing sustainability in municipal solid waste management: an anaerobic-based scenario for Kaunas MBT;geospatial analysis of the degraded areas of Vidzeme and Latgale regions of Latvia;problems of determining wetland boundaries: the case of Lithuania;and the potential of sand – polonite filters for reducing total phosphorus concentration in subsurface horizontal flow constructed wetlands.
While robust model predictive control (MPC) has been studied extensively in recent decades, addressing unmatched disturbances in underactuated robotic systems is still challenging. In this paper, we propose a method t...
详细信息
ISBN:
(纸本)9798350377712;9798350377705
While robust model predictive control (MPC) has been studied extensively in recent decades, addressing unmatched disturbances in underactuated robotic systems is still challenging. In this paper, we propose a method to enhance the robustness of the MPC through the online estimation of disturbances using a nonlinear disturbance observer (NDOB). We call this method disturbance-aware MPC (DA-MPC), because the proposed method explicitly utilizes the estimated disturbance in the future prediction. We provide a performance analysis of the NDOB, establishing the boundedness between the predicted and real states. The main advantages of the DA-MPC include its applicability to real-time control and its compatibility with off-the-shelf optimal control problem (OCP) solvers. We demonstrate the application of the proposed method using an underactuated quadrotor system. The simulation validation shows the effectiveness of the proposed method compared to L-1-adaptive MPC, which is one of the state-of-the-art robust MPC methods.
This paper presents the design and implementation of an innovative control valve system that integrates a ball valve run by a servo motor, IoT capabilities, and PID control for precise operation. The system uses a 1/4...
详细信息
The proceedings contain 214 papers. The topics discussed include: customer intent prediction using sentiment analysis techniques;validation of the global human settlement layer and NASA population data for Ukraine;a c...
ISBN:
(纸本)9781665426053
The proceedings contain 214 papers. The topics discussed include: customer intent prediction using sentiment analysis techniques;validation of the global human settlement layer and NASA population data for Ukraine;a comparison of Kubernetes and Kubernetes-compatible platforms;data mining to achieve quality of life for home automation users;special aspects of errors definition via sum codes within embedded control schemas being realized by means of Boolean complement method;exploiting VPN bonding for time critical video transmission on board drone;adaptive management of digitalization projects for efficiency increasing;NILM application for real time monitoring of appliances energy consumption used;and biometric identification via oculomotor system based on the Volterra model.
In this paper, we propose a lightweight mask detection algorithm and implement an intelligent vehicle system. The algorithm uses YOLOv5s as the backbone network, and at the same time incorporates the SE attention mech...
详细信息
ISBN:
(纸本)9798350381993;9798350382006
In this paper, we propose a lightweight mask detection algorithm and implement an intelligent vehicle system. The algorithm uses YOLOv5s as the backbone network, and at the same time incorporates the SE attention mechanism to optimize the timeliness, and is finally deployed on an intelligent vehicle system with BCM2711 as the controlplatform. Experiments prove that the algorithm proposed in this paper reduces the detection time by 30% while ensuring a higher MAP, which has certain valuefor promotion.
We present BuzzRacer, a palm-sized autonomous vehicle platform suitable for multi-agent autonomous racing. BuzzRacer consists of two parts. First, a software framework with multiple racetrack environments, dynamic sim...
详细信息
ISBN:
(纸本)9798350377712;9798350377705
We present BuzzRacer, a palm-sized autonomous vehicle platform suitable for multi-agent autonomous racing. BuzzRacer consists of two parts. First, a software framework with multiple racetrack environments, dynamic simulation, visualization, and control pipelines. Second, a miniature autonomous vehicle platform capable of 1g acceleration and 3.5m/s top speed. BuzzRacer is an open-source project currently used at Georgia Tech in a project-based robotics course and research projects for experimental validation and benchmarking of novel planning and control algorithms.
In this paper, we propose a method for mobile edge computing (MEC) using unmanned aerial vehicles (UAVs) to enhance wireless connectivity in areas afflicted by natural disasters or obstructed by tall buildings. Despit...
详细信息
ISBN:
(纸本)9798350368130
In this paper, we propose a method for mobile edge computing (MEC) using unmanned aerial vehicles (UAVs) to enhance wireless connectivity in areas afflicted by natural disasters or obstructed by tall buildings. Despite the active research on deep reinforcement learning in recent years, challenges persist in its application to the optimization of cooperative and coordinated behavior among multi-agents. MEC aims to improve efficiency and fairness in offloading from user terminals (UTs) to UAVs while minimizing energy consumption. Therefore, UAV groups must operate independently within designated areas to facilitate connections between UTs and servers. We introduce multi-agent deep deterministic policy gradient to MEC and improve the reward design to achieve high-performance MEC with efficient cooperative behavior only using limited local data. Experimental results demonstrate that our approach significantly enhances MEC efficiency through effective cooperative behavior. Specifically, it offloads more tasks/applications to UAVs compared to baseline methods while reducing energy consumption per offloading.
In this paper, we present a controller framework that synthesizes control policies for Jump Markov Linear systems subject to stochastic mode switches and imperfect mode estimation. Our approach builds on safe and robu...
详细信息
ISBN:
(纸本)9798350377712;9798350377705
In this paper, we present a controller framework that synthesizes control policies for Jump Markov Linear systems subject to stochastic mode switches and imperfect mode estimation. Our approach builds on safe and robust methods for Model Predictive control (MPC), but in contrast to existing approaches that either optimize without regard to feasibility or utilize soft constraints that increase computational requirements, we employ a safe and robust control approach informed by the feasibility of the optimization problem. We formulate and encode finite horizon safety for multiple model systems in our MPC design using control Barrier Functions (CBFs). When subject to inaccurate hybrid state estimation, our feasibility-guided MPC generates a control policy that is maximally robust to uncertainty in the system's modes. We evaluate our approach on an orbital rendezvous problem and a six degree-of-freedom hexacopter under several scenarios and benchmarks to demonstrate the utility of the framework. Results indicate that the proposed technique of maximizing the robustness horizon, and the use of CBFs for safety awareness, improve the overall safety and performance of MPC for Jump Markov Linear systems.
The magnitude frequency-based response data fitting mechanism is available for the case of proper or strictly proper linear and time-invariant (LTI) systems. This paper presents an extension to this mechanism for impr...
详细信息
ISBN:
(纸本)9798350364309;9798350364293
The magnitude frequency-based response data fitting mechanism is available for the case of proper or strictly proper linear and time-invariant (LTI) systems. This paper presents an extension to this mechanism for improper single-input and single-output (SISO) systems described by linear differential-algebraic equations (DAEs). Such descriptor models are computed as the solution to an optimization problem formulated as a Log-Chebyshev approximation, with additionally-imposed upper boundness, stability, and minimum phase constraints, useful in the context of robust synthesis. Moreover, a direct implication of such descriptor systems identification in the robust feedback linearization (RFL) control problem is underlined. A numeric example validates the proposed method of descriptor system identification applied to solve an RFL problem.
暂无评论