Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development ...
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ISBN:
(纸本)9798350364309;9798350364293
Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development of advanced driver assistance systems and autonomous vehicles, relying on precise positioning data for safe navigation. One of the solutions involves using image processing algorithms, which can have two approaches. One approach is decentralized, in which each vehicle performs its own computing steps and determines its position concerning the other nearby vehicles. The second approach, proposed in this paper, is centralized, where each vehicle sends data to a server that uses cloud computing to process all the data in real-time. As such, vehicles can create a more comprehensive view of the driving conditions in the area by using either of these two approaches, which can help them anticipate potential hazards and make more informed decisions.
Embedded systems Week (ESWEEK) is the premier event covering all aspects of hardware and software design for intelligent and connected computingsystems. By bringing together three leading conferences [the Internation...
Embedded systems Week (ESWEEK) is the premier event covering all aspects of hardware and software design for intelligent and connected computingsystems. By bringing together three leading conferences [the internationalconference on Compilers, Architecture, and Synthesis for Embedded systems (CASES); the internationalconference on Hardware/Software Codesign and System Synthesis (CODES+ISSS); and the internationalconference on Embedded Software (EMSOFT)] and a variety of symposia, hot-topic workshops, tutorials, and education classes, ESWEEK presents to the attendees a wide range of topics unveiling state-of-the-art embedded software, embedded architectures, and embedded system designs.
In post-disaster scenarios, field robots and unmanned aerial vehicles (UAVs) are effective tools to provide an ondemand response and guarantee the safety of humans. Sensors, field robots, and the devices equipped by U...
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The agricultural sector continually seeks innovative solutions, and inexperienced farmers do not know how to choose the suitable seed for their agricultural land. This causes unstable crop harvesting and waste of mone...
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computing offload is a key technology in mobile edge computing (MEC). By offloading tasks to the edge servers, it solves the problem that terminal devices in the edge network cannot handle high computing and time sens...
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A quadruped robot faces balancing challenges on a six-degrees-of-freedom moving platform, like subways, buses, airplanes, and yachts, due to independent platform motions and resultant diverse inertia forces on the rob...
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ISBN:
(纸本)9798350377712;9798350377705
A quadruped robot faces balancing challenges on a six-degrees-of-freedom moving platform, like subways, buses, airplanes, and yachts, due to independent platform motions and resultant diverse inertia forces on the robot. To alleviate these challenges, we present the Learning-based Active Stabilization on Moving Platforms (LAS-MP), featuring a self-balancing policy and system state estimators. The policy adaptively adjusts the robot's posture in response to the platform's motion. The estimators infer robot and platform states based on proprioceptive sensor data. For a systematic training scheme across various platform motions, we introduce platform trajectory generation and scheduling methods. Our evaluation demonstrates superior balancing performance across multiple metrics compared to three baselines. Furthermore, we conduct a detailed analysis of the LAS-MP, including ablation studies and evaluation of the estimators, to validate the effectiveness of each component.
Weather forecasting is an important function in a variety of activities such as agriculture, environment monitoring, and disaster management among others. Today with the development of technology, vast amounts of mete...
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Deploying edge servers on Unmanned Aerial Vehicles (UAVs) has become a promising strategy to handle the spatiotemporally varying user demands on ground. However, a critical limitation of the UAVs is the limited flight...
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This paper introduces a generic filter-based state estimation framework that supports two state-decoupling strategies based on cross-covariance factorization. These strategies reduce the computational complexity and i...
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ISBN:
(纸本)9798350377712;9798350377705
This paper introduces a generic filter-based state estimation framework that supports two state-decoupling strategies based on cross-covariance factorization. These strategies reduce the computational complexity and inherently support true modularity - a perquisite for handling and processing meshed range measurements among a time-varying set of devices. In order to utilize these measurements in the estimation framework, positions of newly detected stationary devices (anchors) and the pairwise biases between the ranging devices are required. In this work an autonomous calibration procedure for new anchors is presented, that utilizes range measurements from multiple tags as well as already known anchors. To improve the robustness, an outlier rejection method is introduced. After the calibration is performed, the sensor fusion framework obtains initial beliefs of the anchor positions and dictionaries of pairwise biases, in order to fuse range measurements obtained from new anchors tightly-coupled. The effectiveness of the filter and calibration framework has been validated through evaluations on a recorded dataset and real-world experiments.
To enhance the contour accuracy of biaxial systems, this paper proposes a compensation method that models independent single-axis systems and then couples multiple servo axes through model predictive control algorithm...
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