Development of Sensing Algorithms for Object Tracking …
This article presents the sensing and safety algorithms for autonomous excavators operating on construction sites. Safety is a key concern for autonomous construction to reduce collisions and machinery damage. Taking this point into consideration, our study deals with LiDAR data processing that allows for object detection, motion tracking/prediction, and track management, as well as safety …
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AI, automation, and the future of work: Ten things to
Jun 01, 2018 · Rapid technological progress. Beyond traditional industrial automation and advanced robots, new generations of more capable autonomous systems are appearing in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores. Much of this progress has been driven by improvements in systems and components
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Practical object recognition in autonomous driving and beyond
Junior's autonomous driving systems are based on building detailed maps of the world, then localizing to them during operation. As a result, construction zones present a signifi-cant challenge. Robust detection of traffic cones, construction equipment, or workers holding stop signs could significantly improve handling of these situations.
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A Decision-Making Model for Autonomous Vehicles at Urban
Feb 13, 2021 · The decision-making models that are able to deal with complex and dynamic urban intersections are critical for the development of autonomous vehicles. A key challenge in operating autonomous vehicles robustly is to accurately detect the trajectories of other participants and to consider safety and efficiency concurrently into interactions between vehicles.
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3D-LIDAR Multi Object Tracking for Autonomous Driving
The recent advancement of the autonomous vehicle has raised the need for reliable environmental perception. This is evident, as an autonomous vehicle has to perceive and interpret its local environment in order to execute reactive and predictive control action. Object Tracking is an integral part of vehicle perception, as it enables the vehicle to estimate surrounding objects trajectories to
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Uncertainty Evaluation of Object Detection Algorithms for
Jul 30, 2021 · The safety of the intended functionality (SOTIF) has become one of the hottest topics in the field of autonomous driving. However, no testing and evaluating system for SOTIF performance has been proposed yet. Therefore, this paper proposes a framework based on the advanced You Only Look Once (YOLO) algorithm and the mean Average Precision (mAP) method to evaluate the object …
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Development and evaluation of advanced safety …
Up to12%cash back · Mar 12, 2019 · This study focuses on the development and evaluation of advanced safety algorithms for excavators using virtual reality (VR). An excavator typically operates under a stationary state with its working parts rotating 360° in coordination with nearby workers. During excavation, a fatal accident can occur due to operator carelessness and work site blind spots. …
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Jaho SEO | ResearchGate
This article presents the sensing and safety algorithms for autonomous excavators operating on construction sites. Safety is a key concern for autonomous construction to reduce collisions and
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A Range-Based Algorithm for Autonomous Navigation of …
Sep 17, 2021 · This paper proposes an algorithm that will allow an autonomous aerial drone to approach and follow a steady or moving herd of cattle using only range measurements. The algorithm is also insensitive to the complexity of the herd's movement and the measurement noise. Once arrived at the herd of cattle, the aerial drone can follow it to a desired destination.
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(PDF) Development of Sensing Algorithms for Object
Hence, the proposed algorithms can be applied to diverse autonomous machines for safety enhancement. Overview of the developed predicted safety algorithm. Illustration of í µí±, í µí±
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Learn-To-Race: A Multimodal Control Environment for
safety-critical, sub-second decisions in dynamically unsta-ble contexts, such as autonomous racing, real-time uncer-tainty analysis in highway driving, and trajectory forecast-ing. In this paper, we exemplify algorithm development and benchmarking of methods under learning from demonstra-tions, reinforcement learning, and model-predictive control.
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Experts Release Scorecard for IEEE Computer Society's 2020
Consequently, a significant market increase has recently been predicted for autonomous vehicles and autonomous mobile robots by 2025. However, to increase the autonomy level of such intelligent systems, functional safety and reliability challenges have to be faced. 9. Applying AI to Cybersecurity (B/C).
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Autonomous Vehicles: Partnership for Progress in Image Sensing
Aug 18, 2021 · Northampton, MA --News Direct-- onsemi. As vehicles progress from advanced driver assistance systems (ADAS) to becoming fully autonomous, a key technology enabler will be the advanced sensors that allow these vehicles to sense the world around them. onsemi has a legacy of imaging proficiency spanning over four decades with over 400 million
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Context-Aware Sensor Uncertainty Estimation for …
Oct 25, 2021 · Developments in mobility technology arise from the need to achieve greater independence and safety in ambiguous or challenging situations. The latest revolution in transportation is fully autonomous vehicles (AVs), which are equipped with advanced sensor technology, smart controllers, and intelligent actuators with the aim of providing a hassle-free driving experience for passengers and road
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Review on Machine Learning based algorithms used in
The clustering algorithms are focused on defining the construction from data arguments. It defines the methods Authors have also addressed the challenges of behavioural safety throughout the progress of deep learning tactics in autonomous vehicles. M. Wang, Z. Du and Y. Zhang, "A positioning algorithm of autonomous car based on map
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THE OFFICIAL MAGAZINE OF THE OCEANOGRAPHY SOCIETY
concepts and recent progress toward this principled approach, focusing on reachability, path planning, and adaptive sampling, and presents results of a real-time forecasting and planning experiment completed during February–April 2017 for the Northern Arabian Sea Circulation-autonomous research program. The predictive skill, layered
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Autonomous Vehicle Implementation Predictions
Autonomous Vehicle Implementation Predictions: Implications for Transport Planning Victoria Transport Policy Institute 3 Executive Summary Many decision-makers and practitioners wonder how autonomous (also called self-driving or robotic) vehicles (AVs) will affect future travel, and therefore the need for roads, parking facilities and public transit services, and what public policies can
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Feb 13, 2021 · Path planning is a key technology for autonomous underwater vehicle (AUV) navigation. With the emphasis and research on AUV, AUV path planning technology is continuously developing. Path planning techniques generally include environment modelling methods and path planning algorithms. Based on a brief description of the environment modelling methods, this paper focuses on the path …
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Learn-To-Race: A Multimodal Control Environment for
safety-critical, sub-second decisions in dynamically unsta-ble contexts, such as autonomous racing, real-time uncer-tainty analysis in highway driving, and trajectory forecast-ing. In this paper, we exemplify algorithm development and benchmarking of methods under learning from demonstra-tions, reinforcement learning, and model-predictive control.
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10 Examples of Artificial Intelligence in Construction
Jul 08, 2021 · 10 Examples of AI in Construction. 1. Prevent cost overruns. Most mega projects go over budget despite employing the best project teams. Artificial Neural Networks are used on projects to predict cost overruns based on factors such as project size, contract type and the competence level of project managers.
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