Road networks are a vital part of modern travel;there are currently 21 million kilometers of road networks throughout the world. Using a regression model with an adjusted R2 of 0.90, it is estimated that by 2050, an e...
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ISBN:
(数字)9781665408370
ISBN:
(纸本)9781665408387;9781665408370
Road networks are a vital part of modern travel;there are currently 21 million kilometers of road networks throughout the world. Using a regression model with an adjusted R2 of 0.90, it is estimated that by 2050, an extra 3.0 - 4.7 million km of road will be paved. This brings up the well-explored domain of automating lighting systems. There have been numerous works trying to optimize road lighting systems, but most of them are statically programed or face problems with upscaling. The goal of this paper is to design and implement advanced development in embedded systems for energy conservation in street lights. This work uses a decentralized approach which enables us to control each node /street light individually as well as a group through the use of NRF 24L01 Transceiver module), the Sensing Unit (Ultrasonic sensor HC-SR04), Microcontroller Unit (Arduino Nano), and Lighting system. The design flow takes care of scenarios where if one or more of the nodes/ sensors fail it will not affect the entire row of streetlights. This work aims at creating a dynamically programed automatic street lighting system with the main focus on scalability. Our goal is to create a synchronized array of nodes that may accept new nodes without requiring any changes to the existing nodes. This allows the ability to increase the size of the automation-network ***, the system was conceived and implemented successfully as a prototype for Smart highway lighting system.
Vehicle control algorithms exploiting connectivity and automation, such as Connected and Automated Vehicles (CAVs) or advanced Driver Assistance systems (ADAS), have the opportunity to improve energy savings. However,...
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Vehicle control algorithms exploiting connectivity and automation, such as Connected and Automated Vehicles (CAVs) or advanced Driver Assistance systems (ADAS), have the opportunity to improve energy savings. However, lower levels of automation involve a human-machine interaction stage, where the presence of a human driver affects the performance of the control algorithm in closed loop. This occurs for instance in the case of Eco-Driving control algorithms implemented as a velocity advisory system, where the driver is displayed an optimal speed trajectory to follow to reduce energy consumption. Achieving the control objectives relies on the human driver perfectly following the recommended speed. If the driver is unable to follow the recommended speed, a decline in energy savings and poor vehicle performance may occur. This warrants the creation of models forecast the response of a human driver when operating in the loop with a speed advisory system. This work proposes a sequence to sequence long-short term memory (LSTM)-based driver behavior model to predict the interaction of a human driver to a suggested desired vehicle speed trajectory. A driving simulator is used for data collection and to train the driver model, which is then compared against the driving data and a deterministic model. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)
In the realm of indoor robotics, navigation poses a critical challenge across service robots, humanoids, and warehouse automation. Existing techniques like line following, RFID tracking, and Aruco marker-based systems...
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ISBN:
(数字)9798350360660
ISBN:
(纸本)9798350360677
In the realm of indoor robotics, navigation poses a critical challenge across service robots, humanoids, and warehouse automation. Existing techniques like line following, RFID tracking, and Aruco marker-based systems exhibit limitations in autonomy and adaptability. This has created a need for the development of an advanced and sophisticated autonomous navigation system that encompasses self-reliant perception, planning, and control capabilities. The proposed system makes use of LiDAR technology for mapping and Robot operating system for planning and control which takes place on Jetson Nano GPU platform, providing real-time processing power for environmental data. LiDAR sensors offer accurate environmental perception, obstacle detection, and adaptability to dynamic indoor settings. The system employs BLDC wheels and an aluminium base for versatility, supporting loads up to 120 kg. Additionally, it incorporates an IMU sensor with EKF sensor fusion for accurately estimating the robot's position. This flexible design has applications in various indoor robotics scenarios, ranging from complex service tasks to efficient warehouse operations. This versatile design finds applications in various indoor robotics scenarios, from complex service tasks to efficient warehouse operations.
advanced driver assistance systems (ADASs) support drivers in multipleways, such as adaptive cruise control, lane tracking assistance (LTA), and blind spot monitoring, among other services. However, the use of ADAS cr...
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ISBN:
(纸本)9783031060861;9783031060854
advanced driver assistance systems (ADASs) support drivers in multipleways, such as adaptive cruise control, lane tracking assistance (LTA), and blind spot monitoring, among other services. However, the use of ADAS cruise control has been reported to delay reaction to vehicle collisions. We created a robot human-machine interface (RHMI) to inform drivers of emergencies by means of movement, which would allow drivers to prepare for the disconnection of autonomous driving. This study investigated the effects of RHMI on response to the emergency disconnection of the LTA function of autonomous driving. We also examined drivers' fatigue and arousal using near-infrared spectroscopy (NIRS) on the prefrontal cortex. The participants in this study were 12 males and 15 females. We recorded steering torque and NIRS data in the prefrontal region across two channels during the manipulation of automatic driving with a driving simulator. The scenario included three events in the absence of LTA due to bad weather. All of the participants experienced emergencies with and without RHMI, implemented using two agents: RHMI prototype (RHMI-P) and RoBoHoN. Our RHMI allowed the drivers to respond earlier to emergency LTA disconnection. All drivers showed a gentle torque response for RoBoHoN, but some showed a steep response with RHMI-P and without RHMI. NIRS data showed significant prefrontal cortex activation in RHMI conditions (especially RHMI-P), which may indicate high arousal. Our RHMI helped drivers stay alert and respond to emergency LTA disconnection;however, some drivers showed a quick and large torque response only with RHMI-P.
This study presents the development and implementation of a PID steering controlsystem for lane-keeping assistance using an IMU sensor and ROS (Robot Operating system). The system leverages the capabilities of the Te...
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ISBN:
(数字)9798331504373
ISBN:
(纸本)9798331504380
This study presents the development and implementation of a PID steering controlsystem for lane-keeping assistance using an IMU sensor and ROS (Robot Operating system). The system leverages the capabilities of the Teensy 4.1 microcontroller and the HWT905-TTL IMU sensor to maintain precise steering adjustments, crucial for autonomous vehicle applications. The PID controller, designed to respond dynamically to real-time feedback, ensures that the motor reaches designated target angles, even under varying test conditions. The controlsystem was tuned experimentally to achieve optimal response times, resulting in a rise time of approximately 2 seconds, a steady-state error within ±1-2 degrees, and a maximum overshoot of 4.09%. Performance metrics such as the Integral of Squared Error (ISE) and the Integral of Time-weighted Squared Error (ITSE) further confirmed system accuracy and stability over time. Results indicate that the proposed controlsystem effectively maintains lane-keeping with minimal error, demonstrating potential for future deployment in real-world autonomous driving scenarios. Future work will focus on enhancing system adaptability through advanced tuning techniques and sensor fusion to improve robustness in dynamic environments.
Flexible sensors for hand gesture recognition and human-machine interface (HMI) applications have witnessed tremendous advancements during the last decades. Current state-of-the-art sensors placed on fingers or embedd...
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Flexible sensors for hand gesture recognition and human-machine interface (HMI) applications have witnessed tremendous advancements during the last decades. Current state-of-the-art sensors placed on fingers or embedded into gloves are incapable of fully capturing all hand gestures and are often uncomfortable for the wearer. Herein, a flake-sphere hybrid structure of reduced graphene oxide (rGO) doped with polystyrene (PS) spheres is fabricated to construct the highly sensitive, fast response, and flexible piezoresistive sensor array, which is ultralight in the weight of only 2.8 g and possesses the remarkable curved-surface conformability. The flexible wrist-worn device with a five-sensing array is used to measure pressure distribution around the wrist for accurate and comfortable hand gesture recognition. The intelligent wristband is able to classify 12 hand gestures with 96.33% accuracy for five participants using a machine learning algorithm. To showcase our wristband, a real-time system is developed to control a robotic hand via the classification results, which further demonstrates the potential of this work for HMI applications.
Drilling fluid, as a critical element of drilling engineering, requires accurate performance detection to ensure drilling safety and efficiency. Traditional detection technologies exhibit limitations such as insuffici...
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ISBN:
(数字)9798331535087
ISBN:
(纸本)9798331535094
Drilling fluid, as a critical element of drilling engineering, requires accurate performance detection to ensure drilling safety and efficiency. Traditional detection technologies exhibit limitations such as insufficient accuracy and complex operations when addressing complex downhole environments. To enhance the efficiency and precision of oilfield drilling fluid detection, this study designs a detection system based on a six-speed rotational viscometer. The system employs a six-speed rotational viscometer as the core measurement device, integrated with sensors and data acquisition cards, enabling rapid and accurate measurement of drilling fluid rheological properties. Performance testing reveals measurement errors ranging from 0.07% to 0.5%, demonstrating excellent precision, stability, and repeatability. The results confirm that this system effectively meets practical requirements for oilfield drilling fluid detection and provides reliable technical support for drilling operations.
This paper proposes a low-power capacitive sensorinterface using novel time-compensation technique to eliminate the effect of stray capacitance. The interface comprises a capacitance-to-current converter charging a l...
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ISBN:
(纸本)9781665424615
This paper proposes a low-power capacitive sensorinterface using novel time-compensation technique to eliminate the effect of stray capacitance. The interface comprises a capacitance-to-current converter charging a load capacitor and a time-compensation controlsystem. Even with large stray capacitance, the controlsystem will adjust the charging time, thereby ensuring the same measurement. Besides, the system only requires a few switches and two comparators which makes this technique unique regarding simplicity, low-cost of power and chip area. To prove the idea, the circuit was designed and simulated using 0.18 mu m standard CMOS technology powered from +/- 1V supply. It accomplishes 125kHz measuring frequency, +/- 1pF capacitance variation, and a sensitivity of 0.5mV/fF with only 30 mu W average power consumption. The simulation also shows an accurate output result within 1% difference between 6pF parasitic capacitance and no parasitic.
Haptic technology enables robots to touch and understand the interactions between objects in the reality. advanced haptic sensing systems can not only collect pressure, temperature and stiffness of touched objects, bu...
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ISBN:
(纸本)9798350333398
Haptic technology enables robots to touch and understand the interactions between objects in the reality. advanced haptic sensing systems can not only collect pressure, temperature and stiffness of touched objects, but also avoid destructive operations, and assist in navigation and posture control for robots. In order to smoothly interact with different types of objects, in the haptic system, it is necessary to develop haptic object recognition methods for effective haptic perception capability. However, compared to RGB images, haptic images collected by optically-based haptic sensors are similar in appearance, which makes traditional convolutional neural networks (e.g.,ResNet, VGG, etc.) ineffective. Therefore, in this paper, we are inspired by popular attention mechanism and multi-scale strategies, and propose a cross-scale attention based haptic object recognition network for object-robot interaction. In particular, On the one hand, we design a cross-scale attention module in convolutional neural networks to acquire spatial contextual feature. On the other hand, we design a learnable bilinear fusion strategy to integrate above spatial contextual feature with original haptic feature, so as to effectively discriminate haptic images. Experimental results on ViTac dataset have shown the effectiveness of our approach.
Typically, egg incubators available for purchase utilize on-off control to regulate incandescent lamps, which might result in temperature changes. The objective of this research is to develop a temperature control sys...
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ISBN:
(数字)9798350368918
ISBN:
(纸本)9798350368925
Typically, egg incubators available for purchase utilize on-off control to regulate incandescent lamps, which might result in temperature changes. The objective of this research is to develop a temperature controlsystem for the incubation of chicken or duck eggs using PID control with graphical user interface and monitor the humidity level. The DHT11 sensor detects the current temperature and humidity. The target temperature are 37 degrees celsius. The process of temperature regulation is achieved by implementing PID control to adjust the power supply of the incandescent lamp in order to maintain a stable desired temperature. The actual humidity will show in GUI then the user could set on / off the mist maker to disperse water, in conjunction with an exhaust fan. The microcontroller used is the Arduino Nano. The Python QML programming language is used to develop a graphical user interface (GUI) for real-time monitoring and control of temperature and humidity conditions. This interface allows for the adjustment of setpoint settings and PID control parameters. Simulation and validation have been conducted in the context of temperature control. The system has rise time of 47s, settling time of 411s and maximum overshoot of 2,64%. The system has the capability to regulate temperature (37 degrees Celsius) with slight fluctuations.
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