19,360 research outputs found
From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation
Context: Competitions for self-driving cars facilitated the development and
research in the domain of autonomous vehicles towards potential solutions for
the future mobility.
Objective: Miniature vehicles can bridge the gap between simulation-based
evaluations of algorithms relying on simplified models, and those
time-consuming vehicle tests on real-scale proving grounds.
Method: This article combines findings from a systematic literature review,
an in-depth analysis of results and technical concepts from contestants in a
competition for self-driving miniature cars, and experiences of participating
in the 2013 competition for self-driving cars.
Results: A simulation-based development platform for real-scale vehicles has
been adapted to support the development of a self-driving miniature car.
Furthermore, a standardized platform was designed and realized to enable
research and experiments in the context of future mobility solutions.
Conclusion: A clear separation between algorithm conceptualization and
validation in a model-based simulation environment enabled efficient and
riskless experiments and validation. The design of a reusable, low-cost, and
energy-efficient hardware architecture utilizing a standardized
software/hardware interface enables experiments, which would otherwise require
resources like a large real-scale test track.Comment: 17 pages, 19 figues, 2 table
Marquette Interchange Perpetual Pavement Instrumentation Project - Phase II
This report presents findings from the second phase of the Marquette Interchange instrumentation project and focuses on the maintenance of data recordation systems, development of computer programs to analyze data, and development of data packages for redistribution. The product of this research is a set of data which includes dynamic pavement response due to live traffic, vehicle information (weight, class, length, et cetera), and environmental data for the test site. The tasks within this project were not oriented for findings regarding pavement performance, but important and helpful conclusions can be drawn for similar future projects. The recordation systems have been maintained and recordation has been continuous. A handful of sensors did require attention and only a fraction of the critical strain sensors have ceased to function, making the project a success. The results of the computer programs written to analyze data show that reasonable accuracy has been achieved. Future work can help to generate more intricate programming making the processes more accurate
Local Motion Planner for Autonomous Navigation in Vineyards with a RGB-D Camera-Based Algorithm and Deep Learning Synergy
With the advent of agriculture 3.0 and 4.0, researchers are increasingly
focusing on the development of innovative smart farming and precision
agriculture technologies by introducing automation and robotics into the
agricultural processes. Autonomous agricultural field machines have been
gaining significant attention from farmers and industries to reduce costs,
human workload, and required resources. Nevertheless, achieving sufficient
autonomous navigation capabilities requires the simultaneous cooperation of
different processes; localization, mapping, and path planning are just some of
the steps that aim at providing to the machine the right set of skills to
operate in semi-structured and unstructured environments. In this context, this
study presents a low-cost local motion planner for autonomous navigation in
vineyards based only on an RGB-D camera, low range hardware, and a dual layer
control algorithm. The first algorithm exploits the disparity map and its depth
representation to generate a proportional control for the robotic platform.
Concurrently, a second back-up algorithm, based on representations learning and
resilient to illumination variations, can take control of the machine in case
of a momentaneous failure of the first block. Moreover, due to the double
nature of the system, after initial training of the deep learning model with an
initial dataset, the strict synergy between the two algorithms opens the
possibility of exploiting new automatically labeled data, coming from the
field, to extend the existing model knowledge. The machine learning algorithm
has been trained and tested, using transfer learning, with acquired images
during different field surveys in the North region of Italy and then optimized
for on-device inference with model pruning and quantization. Finally, the
overall system has been validated with a customized robot platform in the
relevant environment
Wide area detection system: Conceptual design study
An integrated sensor for traffic surveillance on mainline sections of urban freeways is described. Applicable imaging and processor technology is surveyed and the functional requirements for the sensors and the conceptual design of the breadboard sensors are given. Parameters measured by the sensors include lane density, speed, and volume. The freeway image is also used for incident diagnosis
Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping
Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD
Proceedings of the 4th field robot event 2006, Stuttgart/Hohenheim, Germany, 23-24th June 2006
Zeer uitgebreid verslag van het 4e Fieldrobotevent, dat gehouden werd op 23 en 24 juni 2006 in Stuttgart/Hohenhei
Transition Detection at Cryogenic Temperatures Using a Carbon-Based Resistive Heating Layer Coupled with Temperature Sensitive Paint
This paper will highlight the development and application of a carbon-based resistive heating layer for use in transition detection at cryogenic temperatures at the National Transonic Facility (NTF) for full-flight Reynolds number testing. This study builds upon previous work that was successfully demonstrated at the 0.3-m Transonic Cryogenic Tunnel on a smaller-scale airfoil shape of regular geometry. However, the test performed at the NTF involved a semispan wing with complex geometry and significantly larger than previous tests. This required the development of new coatings to provide suitable resistances to provide adequate heating rates for transition detection. Successful implementation of this technology has the ability to greatly enhance transition detection experiments at cryogenic temperatures as well as reducing perturbation in the tunnel caused by more traditional transition detection methods
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