scholarly journals Low-Cost Curb Detection and Localization System Using Multiple Ultrasonic Sensors

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1389 ◽  
Author(s):  
Joon Rhee ◽  
Jiwon Seo
Keyword(s):  
High Performance ◽  
Low Cost ◽  
Autonomous Vehicle ◽  
Distance Estimation ◽  
Autonomous Driving ◽  
Ultrasonic Sensors ◽  
Localization System ◽  
Processing Algorithms ◽  
Detection And Localization ◽  
Localization Systems

Curb detection and localization systems constitute an important aspect of environmental recognition systems of autonomous driving vehicles. This is because detecting curbs can provide information about the boundary of a road, which can be used as a safety system to prevent unexpected intrusions into pedestrian walkways. Moreover, curb detection and localization systems enable the autonomous vehicle to recognize the surrounding environment and the lane in which the vehicle is driving. Most existing curb detection and localization systems use multichannel light detection and ranging (lidar) as a primary sensor. However, although lidar demonstrates high performance, it is too expensive to be used for commercial vehicles. In this paper, we use ultrasonic sensors to implement a practical, low-cost curb detection and localization system. To compensate for the relatively lower performance of ultrasonic sensors as compared to other higher-cost sensors, we used multiple ultrasonic sensors and applied a series of novel processing algorithms that overcome the limitations of a single ultrasonic sensor and conventional algorithms. The proposed algorithms consisted of a ground reflection elimination filter, a measurement reliability calculation, and distance estimation algorithms corresponding to the reliability of the obtained measurements. The performance of the proposed processing algorithms was demonstrated by a field test under four representative curb scenarios. The availability of reliable distance estimates from the proposed methods with three ultrasonic sensors was significantly higher than that from the other methods, e.g., 92.08% vs. 66.34%, when the test vehicle passed a trapezoidal-shaped road shoulder. When four ultrasonic sensors were used, 96.04% availability and 13.50 cm accuracy (root mean square error) were achieved.

scholarly journals A Review of Self-Coherent Optical Transceivers: Fundamental Issues, Recent Advances, and Research Directions

2021 ◽  
Vol 11 (16) ◽  
pp. 7554
Author(s):  
Isiaka Alimi ◽  
Romil Patel ◽  
Nuno Silva ◽  
Chuanbowen Sun ◽  
Honglin Ji ◽  
...  
Keyword(s):  
High Speed ◽  
High Performance ◽  
Low Cost ◽  
Dynamic Environment ◽  
Digital Signal ◽  
Research Directions ◽  
Recent Advances ◽  
Heterogeneous Nature ◽  
Signal Processing Algorithms ◽  
Processing Algorithms

This paper reviews recent progress on different high-speed optical short- and medium-reach transmission systems. Furthermore, a comprehensive tutorial on high-performance, low-cost, and advanced optical transceiver (TRx) paradigms is presented. In this context, recent advances in high-performance digital signal processing algorithms and innovative optoelectronic components are extensively discussed. Moreover, based on the growing increase in the dynamic environment and the heterogeneous nature of different applications and services to be supported by the systems, we discuss the reconfigurable and sliceable TRxs that can be employed. The associated technical challenges of various system algorithms are reviewed, and we proffer viable solutions to address them.

A detailed approach to autonomous vehicle control through Ros and Pixhawk controllers

2021 ◽  
Author(s):  
Brian Quinn ◽  
Jordan Bates ◽  
Michael Parker ◽  
Sally Shoop
Keyword(s):  
Low Cost ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Main Concept ◽  
Robot Operating System ◽  
Military Vehicle ◽  
Minimal Modification ◽  
Wire System ◽  
Utility Vehicle ◽  
Driving Capability

A Polaris MRZR military utility vehicle was used as a testing platform to develop a novel, low cost yet feature-rich, approach to adding remote operation and autonomous driving capability to a military vehicle. The main concept of operation adapts steering and throttle output from a low cost commercially available Pixhawk autopilot controller and translates the signal into the necessary inputs for the Robot Operating System (ROS) based drive by wire system integrated into the MRZR. With minimal modification these enhancements could be applied to any vehicle with similar ROS integration. This paper details the methods and testing approach used to develop this autonomous driving capability.

scholarly journals High Definition Map-Based Localization Using ADAS Environment Sensors for Application to Automated Driving Vehicles

2020 ◽  
Vol 10 (14) ◽  
pp. 4924
Author(s):  
Donghoon Shin ◽  
Kang-moon Park ◽  
Manbok Park
Keyword(s):  
High Performance ◽  
Low Cost ◽  
Autonomous Driving ◽  
Feature Representation ◽  
Map Matching ◽  
Localization Algorithm ◽  
Automated Driving ◽  
High Definition ◽  
Vehicle Position ◽  
Near Future

This paper presents high definition (HD) map-based localization using advanced driver assistance system (ADAS) environment sensors for application to automated driving vehicles. A variety of autonomous driving technologies are being developed using expensive and high-performance sensors, but limitations exist due to several practical issues. In respect of the application of autonomous driving cars in the near future, it is necessary to ensure autonomous driving performance by effectively utilizing sensors that are already installed for ADAS purposes. Additionally, the most common localization algorithm, which is usually used lane information only, has a highly unstable disadvantage in the absence of that information. Therefore, it is essential to ensure localization performance with other road features such as guardrails when there are no lane markings. In this study, we would like to propose a localization algorithm that could be implemented in the near future by using low-cost sensors and HD maps. The proposed localization algorithm consists of several sections: environment feature representation with low-cost sensors, digital map analysis and application, position correction based on map-matching, designated validation gates, and extended Kalman filter (EKF)-based localization filtering and fusion. Lane information is detected by monocular vision in front of the vehicle. A guardrail is perceived by radar by distinguishing low-speed object measurements and by accumulating several steps to extract wall features. These lane and guardrail information are able to correct the host vehicle position by using the iterative closest point (ICP) algorithm. The rigid transformation between the digital high definition map (HD map) and environment features is calculated through ICP matching. Each corrected vehicle position by map-matching is selected and merged based on EKF with double updating. The proposed algorithm was verified through simulation based on actual driving log data.

scholarly journals Processor-in-the-Loop Architecture Design and Experimental Validation for an Autonomous Racing Vehicle

2021 ◽  
Vol 11 (16) ◽  
pp. 7225
Author(s):  
Eugenio Tramacere ◽  
Sara Luciani ◽  
Stefano Feraco ◽  
Angelo Bonfitto ◽  
Nicola Amati
Keyword(s):  
Real Time ◽  
Personal Computer ◽  
Trajectory Planning ◽  
Autonomous Vehicles ◽  
High Performance ◽  
Experimental Validation ◽  
Low Cost ◽  
Autonomous Driving ◽  
Obstacle Detection ◽  
System Level

Self-driving vehicles have experienced an increase in research interest in the last decades. Nevertheless, fully autonomous vehicles are still far from being a common means of transport. This paper presents the design and experimental validation of a processor-in-the-loop (PIL) architecture for an autonomous sports car. The considered vehicle is an all-wheel drive full-electric single-seater prototype. The retained PIL architecture includes all the modules required for autonomous driving at system level: environment perception, trajectory planning, and control. Specifically, the perception pipeline exploits obstacle detection algorithms based on Artificial Intelligence (AI), and the trajectory planning is based on a modified Rapidly-exploring Random Tree (RRT) algorithm based on Dubins curves, while the vehicle is controlled via a Model Predictive Control (MPC) strategy. The considered PIL layout is implemented firstly using a low-cost card-sized computer for fast code verification purposes. Furthermore, the proposed PIL architecture is compared in terms of performance to an alternative PIL using high-performance real-time target computing machine. Both PIL architectures exploit User Datagram Protocol (UDP) protocol to properly communicate with a personal computer. The latter PIL architecture is validated in real-time using experimental data. Moreover, they are also validated with respect to the general autonomous pipeline that runs in parallel on the personal computer during numerical simulation.

scholarly journals A Low-Cost Indoor Activity Monitoring System for Detecting Frailty in Older Adults

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 452 ◽  
Author(s):  
Thomas Tegou ◽  
Ilias Kalamaras ◽  
Markos Tsipouras ◽  
Nikolaos Giannakeas ◽  
Kostantinos Votis ◽  
...  
Keyword(s):  
Older People ◽  
Indoor Localization ◽  
Low Cost ◽  
Clinical Status ◽  
Localization System ◽  
Frailty Status ◽  
Asset Tracking ◽  
Commercial Applications ◽  
Tracking Device ◽  
Localization Systems

Indoor localization systems have already wide applications mainly for providing localized information and directions. The majority of them focus on commercial applications providing information such us advertisements, guidance and asset tracking. Medical oriented localization systems are uncommon. Given the fact that an individual’s indoor movements can be indicative of his/her clinical status, in this paper we present a low-cost indoor localization system with room-level accuracy used to assess the frailty of older people. We focused on designing a system with easy installation and low cost to be used by non technical staff. The system was installed in older people houses in order to collect data about their indoor localization habits. The collected data were examined in combination with their frailty status, showing a correlation between them. The indoor localization system is based on the processing of Received Signal Strength Indicator (RSSI) measurements by a tracking device, from Bluetooth Beacons, using a fingerprint-based procedure. The system has been tested in realistic settings achieving accuracy above 93% in room estimation. The proposed system was used in 271 houses collecting data for 1–7-day sessions. The evaluation of the collected data using ten-fold cross-validation showed an accuracy of 83% in the classification of a monitored person regarding his/her frailty status (Frail, Pre-frail, Non-frail).

Automobile Reversing Radar Based on Ultrasonic Wave

2011 ◽  
Vol 383-390 ◽  
pp. 366-371
Author(s):  
Xin Na Wang ◽  
Qian Gao ◽  
Ping Chuan Zhang
Keyword(s):  
System Design ◽  
Ultrasonic Wave ◽  
High Performance ◽  
Low Cost ◽  
Distance Measurement ◽  
Ultrasonic Sensors ◽  
Détection Signal ◽  
Detection Range ◽  
Detection Signal

Automobile reversing process should be paying more attention for security. This paper analyzes the principle of ultrasonic distance measurement, made simple and practical automobile reversing radar, in which the SPCE061A MCU / DSP of high-performance 16-bit microprocessor was used as the control core and the ultrasonic sensors modular for detection signal. The system design is the modularization structure, so as to simplify the debugging effort, well done eventually reversing radar. The experiments shows that the detection range may be up to 15cm-200cm, the error of distance is only 5cm, fully meet the practical requirements, and low cost.

Real-Time Image and Video Processing Using High-Level Synthesis (HLS)

2017 ◽  
pp. 390-408
Author(s):  
Murad Qasaimeh ◽  
Ehab Najeh Salahat
Keyword(s):  
Video Processing ◽  
High Performance ◽  
Low Cost ◽  
Optimization Techniques ◽  
High Level Synthesis ◽  
Image And Video Processing ◽  
Digital Hardware ◽  
Processing Algorithms ◽  
Computationally Intensive ◽  
High Level

Implementing high-performance, low-cost hardware accelerators for the computationally intensive image and video processing algorithms has attracted a lot of attention in the last 20 years. Most of the recent research efforts were trying to figure out new design automation methods to fill the gap between the ability of realizing efficient accelerators in hardware and the tight performance requirements of the complex image processing algorithms. High-Level synthesis (HLS) is a new method to automate the design process by transforming high-level algorithmic description into digital hardware while satisfying the design constraints. This chapter focuses on evaluating the suitability of using HLS as a new tool to accelerate the most demanding image and video processing algorithms in hardware. It discusses the gained benefits and current limitations, the recent academic and commercial tools, the compiler's optimization techniques and four case studies.

Real-Time Image and Video Processing Using High-Level Synthesis (HLS)

2018 ◽  
pp. 1004-1022
Author(s):  
Murad Qasaimeh ◽  
Ehab Najeh Salahat
Keyword(s):  
Video Processing ◽  
High Performance ◽  
Low Cost ◽  
Optimization Techniques ◽  
High Level Synthesis ◽  
Image And Video Processing ◽  
Digital Hardware ◽  
Processing Algorithms ◽  
Computationally Intensive ◽  
High Level

Implementing high-performance, low-cost hardware accelerators for the computationally intensive image and video processing algorithms has attracted a lot of attention in the last 20 years. Most of the recent research efforts were trying to figure out new design automation methods to fill the gap between the ability of realizing efficient accelerators in hardware and the tight performance requirements of the complex image processing algorithms. High-Level synthesis (HLS) is a new method to automate the design process by transforming high-level algorithmic description into digital hardware while satisfying the design constraints. This chapter focuses on evaluating the suitability of using HLS as a new tool to accelerate the most demanding image and video processing algorithms in hardware. It discusses the gained benefits and current limitations, the recent academic and commercial tools, the compiler's optimization techniques and four case studies.

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