In this paper, we present a novel Reduced Robustified NMPC (R²NMPC) algorithm that has the same complexity as an equivalent nominal NMPC while enhancing it with robustified constraints based on the dynamics of el...
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In this paper, we present a novel Reduced Robustified NMPC (R²NMPC) algorithm that has the same complexity as an equivalent nominal NMPC while enhancing it with robustified constraints based on the dynamics of ellipsoidal uncertainty sets. This promises both a closed-loop- and constraint satisfaction performance equivalent to common Robustified NMPC approaches while drastically reducing the computational complexity. The main idea lies in approximating the ellipsoidal uncertainty sets propagation over the prediction horizon with the system dynamics’ sensitivities inferred from the last optimal control problem (OCP) solution and similarly for the gradients to robustify the constraints. Thus, we do not require the decision variables related to the uncertainty propagation within the OCP, rendering it computationally tractable. Next, we illustrate the real-time control capabilities of our algorithm in handling a complex, high-dimensional, and highly nonlinear system, namely the trajectory following of an autonomous passenger vehicle modeled with a dynamic nonlinear single-track model. Our experimental findings, alongside a comparative assessment against other Robust NMPC approaches, affirm the robustness of our method in effectively tracking an optimal racetrack trajectory while satisfying the nonlinear constraints. This performance is achieved while fully utilizing the vehicle's interface limits, even at high speeds of up to 37.5m s −1 , and successfully managing state estimation disturbances. Our approach maintains a mean solving frequency of 140Hz. The code used in this research is publicly accessible as open-source software: https://***/bzarr/TUM-CONTROL
This study aimed to develop and evaluate a costeffective Inertial Measurement Unit (IMU) system for gait analysis, comparing its performance with the Vicon system and the VideoPose3D algorithm. The system comprises fi...
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In human-human interaction, posture serves as a critical non-verbal cue that subconsciously shapes first impressions and perceptions. Given the preference for anthropomorphism of robots acting in socially intensive si...
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ISBN:
(数字)9798350373578
ISBN:
(纸本)9798350373585
In human-human interaction, posture serves as a critical non-verbal cue that subconsciously shapes first impressions and perceptions. Given the preference for anthropomorphism of robots acting in socially intensive situations such as caregiving, the influence of posture is expected to increase in interactions with humanoid robots. This study aims to identify the most preferred default position for the assistive humanoid robot GARMI, ensuring users’ perceived safety in human-robot interaction (HRI). In a preliminary study, 30 participants evaluated ten different arm postures of the robot GARMI regarding their perceived discomfort. From these evaluations and direct rankings, three arm positions were selected for further analysis alongside the current default position in the virtual reality (VR) study. In this subsequent study, 50 participants assessed their perception of safety using both objective measures of comfort distance, grounded in proxemic theory, and two subjective measures, i.e., Godspeed questionnaire and Robotic Social Attribute Scale (RoSaS). The results indicate a significant impact of the robot’s arm postures on users’ perceived safety. A polite, butler-like posture is recommended as the default position, aligning with the role users typically attribute to the robot GARMI.
Emerging devices are susceptible to manufacturing defects due to immature fabrication processes. Ferroelectric field-effect transistors, referred to as FeFETs, are promising emerging devices, but the impact of manufac...
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Effective pest detection and identification are of great significance for agricultural activities, and morden machine learning methods, especially the deep neural network, undoubtedly provide convenient and effective ...
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This research aims to investigate professional racing drivers’ expertise to develop an understanding of their cognitive and adaptive skills to create new autonomy algorithms. An expert interview study was conducted w...
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ISBN:
(数字)9798350348811
ISBN:
(纸本)9798350348828
This research aims to investigate professional racing drivers’ expertise to develop an understanding of their cognitive and adaptive skills to create new autonomy algorithms. An expert interview study was conducted with 11 professional race drivers, data analysts, and racing instructors from across prominent racing leagues. The interviews were conducted using an exploratory, non-standardized expert interview format guided by a set of prepared questions. The study investigates drivers’ exploration strategies to reach their vehicle limits and contrasts them with the capabilities of state-of-the-art autonomous racing software stacks. Participants were questioned about the techniques and skills they have developed to quickly approach and maneuver at the vehicle limit, ultimately minimizing lap times. The analysis of the interviews was grounded in Mayring’s qualitative content analysis framework, which facilitated the organization of the data into multiple categories and subcategories. Our findings create insights into human behavior regarding reaching a vehicle’s limit and minimizing lap times. We conclude from the findings the development of new autonomy software modules that allow for more adaptive vehicle behavior. By emphasizing the distinct nuances between manual and autonomous driving techniques, the paper encourages further investigation into human drivers’ strategies to maximize their vehicles’ capabilities.
This work focuses on the agile transportation of liquids with robotic manipulators. In contrast to existing methods that are either computationally heavy, system/container specific or dependant on a singularity-prone ...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
This work focuses on the agile transportation of liquids with robotic manipulators. In contrast to existing methods that are either computationally heavy, system/container specific or dependant on a singularity-prone pendulum model, we present a real-time slosh-free tracking technique. This method solely requires the reference trajectory and the robot’s kinematic constraints to output kinematically feasible joint space commands. The crucial element underlying this approach consists on mimicking the end-effector’s motion through a virtual quadrotor, which is inherently slosh-free and differentially flat, thereby allowing us to calculate a slosh-free reference orientation. Through the utilization of a cascaded proportional-derivative (PD) controller, this slosh-free reference is transformed into task space acceleration commands, which, following the resolution of a Quadratic Program (QP) based on Resolved Acceleration Control (RAC), are translated into a feasible joint configuration. The validity of the proposed approach is demonstrated by simulated and real-world experiments on a 7 DoF Franka Emika Panda robot.
Pneumonia is a serious disease that can be fatal,particularly among children and the *** accuracy of pneumonia diagnosis can be improved by combining artificial-intelligence technology with X-ray *** study proposes X-...
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Pneumonia is a serious disease that can be fatal,particularly among children and the *** accuracy of pneumonia diagnosis can be improved by combining artificial-intelligence technology with X-ray *** study proposes X-ODFCANet,which addresses the issues of low accuracy and excessive parameters in existing deep-learningbased pneumonia-classification *** network incorporates a feature coordination attention module and an omni-dimensional dynamic convolution(ODConv)module,leveraging the residual module for feature extraction from X-ray *** feature coordination attention module utilizes two one-dimensional feature encoding processes to aggregate feature information from different spatial ***,the ODConv module extracts and fuses feature information in four dimensions:the spatial dimension of the convolution kernel,input and output channel quantities,and convolution kernel *** experimental results demonstrate that the proposed method can effectively improve the accuracy of pneumonia classification,which is 3.77%higher than that of *** model parameters are 4.45M,which was reduced by approximately 2.5 *** code is available at https://***/limuni/X ODFCA NET.
Existing crowd counting techniques have achieved significant progress with the emergence of deep learning. During development, emerging crowd counting methods have generally become more and more complex and enormous, ...
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Modeling the kinematics and dynamics of UAVs with cable-suspended loads using dual quaternions remains an area requiring further exploration, especially when considering the offset between the attachment point and the...
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ISBN:
(数字)9798331513283
ISBN:
(纸本)9798331513290
Modeling the kinematics and dynamics of UAVs with cable-suspended loads using dual quaternions remains an area requiring further exploration, especially when considering the offset between the attachment point and the UAV's center of mass. This work introduces a novel control strategy based on dual quaternions for sling load cargo UAV (cUAV) systems with offset attachments. Leveraging the mathematical efficiency and compactness of dual quaternions, we establish a unified representation of the kinematics and dynamics of both the UAV and its suspended load. Extensive simulations and realworld experiments were conducted to evaluate the accuracy and robustness of the proposed strategy. The results demonstrate the controller's reliability and stability across various conditions in practical cUAV applications. This study makes a contribution to the presentation of this novel control strategy that harnesses the benefits of dual quaternions for cUAVs. Our work also holds promise for inspiring future innovations in under-actuated systems control using dual quaternions.
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