The intricate and multi-stage task in dynamic public spaces like luggage trolley collection in airports presents both a promising opportunity and an ongoing challenge for automated service robots. Previous research ha...
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In this study, we tackle the complex task of enabling prosthetic hands to accurately reproduce sounds, a crucial aspect for distinguishing between different materials through auditory feedback. Sound identification, s...
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ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
In this study, we tackle the complex task of enabling prosthetic hands to accurately reproduce sounds, a crucial aspect for distinguishing between different materials through auditory feedback. Sound identification, such as discerning a drywall tap from that on a brick wall, significantly enhances the functionality and user experience of prosthetic devices. However, achieving this level of auditory feedback in prosthetic hands poses considerable challenges. We utilize reinforcement learning (RL) techniques to train prosthetic hands in emulating human-like sound characteristics, focusing on key auditory signals like amplitude and onset timing. Our approach integrates a detailed analysis of these sound attributes to direct the prosthetic hand’s movements for the sound generation that mimics natural human actions. We developed a tailored reward function incorporating amplitude, onset strength, and timing criteria to ensure the prosthetic hand’s movements align closely with the intended human-like sound output.
Autonomous driving is a highly anticipated approach toward eliminating roadway fatalities. At the same time, the bar for safety is both high and costly to verify. This work considers the role of remotely-located human...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Autonomous driving is a highly anticipated approach toward eliminating roadway fatalities. At the same time, the bar for safety is both high and costly to verify. This work considers the role of remotely-located human operators supervising a fleet of autonomous vehicles (AVs) for safety. Such a ‘scalable supervision’ concept was previously proposed to bridge the gap between still-maturing autonomy technology and the pressure to begin commercial offerings of autonomous driving. The present article proposes DISCES, a framework for Data-Informed Safety-Critical Event Simulation, to investigate the practicality of this concept from a dynamic network loading standpoint. With a focus on the safety-critical context of AVs merging into mixed-autonomy traffic, vehicular arrival processes at 1,097 highway merge points are modeled using microscopic traffic reconstruction with historical data from interstates across three California counties. Combined with a queuing theoretic model, these results characterize the dynamic supervision requirements and thereby scalability of the teleoperation approach. Across all scenarios we find reductions in operator requirements greater than 99% as compared to in-vehicle supervisors for the time period analyzed. The work also demonstrates two methods for reducing these empirical supervision requirements: (i) the use of cooperative connected AVs — which are shown to produce an average 3.67 orders-of-magnitude system reliability improvement across the scenarios studied — and (ii) aggregation across larger regions.
In this paper, we consider the analysis and control of continuous-time nonlinear systems to ensure universal shifted stability and performance, i.e., stability and performance w.r.t. each forced equilibrium point of t...
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The Internet of Things (IoT) has grown rapidly in recent years, intending to affect everything from everyday life to large industrial systems. Regrettably, this has attracted the attention of hackers, who have turned ...
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This paper presents a review on methods for class-imbalanced learning with the Support Vector Machine (SVM) and its variants. We first explain the structure of SVM and its variants and discuss their inefficiency in le...
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Power quality challenges have generated a lot of disputes between utilities,customers,network operators,and equipment manufacturers around the world as regards the share of responsibility for power quality solutions,t...
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Power quality challenges have generated a lot of disputes between utilities,customers,network operators,and equipment manufacturers around the world as regards the share of responsibility for power quality solutions,this results in different levels of financial and technical losses for both the network operators and the *** of the major consequences of the operation of heavy-duty factories globally is the corruption of power quality at the point of common coupling(PCC).In order to quantify the harmonics contribution at the PCC by industrial consumers,this paper presents three-phase total harmonics distortion of current(THDi)prediction model at the *** proposed artificial neural network(ANN)models use a multilayer perceptron neural network(MLPN)to predict three-phase total harmonic *** input parameter used in the models is easily measured with basic power *** model was trained with input parameters captured at 33 kV and 132 kV voltage levels using power quality meters at five(5)different steel manufacturing ***(8)different models were designed,trained,validated,and tested with different combinations of input parameters,number of hidden layers,and number of neurons in the hidden *** results show that the model with two hidden layers which uses four major power parameters(Current,apparent power,reactive and active power)as input parameters in the training model had the best performance with a 95.5%coefficient of correlation between the measured THDi and the predicted THDi.
Structural health monitoring (SHM) was developed to provide diagnosis of the state of civil structures, such as bridge and building, throughout their lifespan. The superstructure degrades over time mainly because of t...
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This paper presents a multi-layer software architecture to perform cooperative missions with a fleet of quad-rotors providing support in electrical power line inspection operations. The proposed software framework gua...
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