JOMS:System Architecture for Telemetry and Visualization on Unmanned Vehicle

Hasnan, Khalid; Saesar, Luhur Budi; Ikhmatiar, Mohammad Sibghotulloh; Herawan, Tutut

doi:10.1016/j.proeng.2012.01.591

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Multiple road conditions studies are incomplete. No overall consideration is given to factors such as road environment, weather conditions, the influence of personnel in the environment, and the fastest response speed of vehicles 8 – 11 .…”

Section: Introductionmentioning

confidence: 99%

Study on a risk model for prediction and avoidance of unmanned environmental hazard

Qiu

Zhang

et al. 2022

Sci Rep

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Comprehensive research is conducted on the design and control of the unmanned systems for electric vehicles. The environmental risk prediction and avoidance system is divided into the prediction part and the avoidance part. The prediction part is divided into environmental perception, environmental risk assessment, and risk prediction. In the avoidance part, according to the risk prediction results, a conservative driving strategy based on speed limit is adopted. Additionally, the core function is achieved through the target detection technology based on deep learning algorithm and the data conclusion based on deep learning method. Moreover, the location of bounding box is further optimized to improve the accuracy of SSD target detection method based on solving the problem of imbalanced sample categories. Software such as MATLAB and CarSim are applied in the system. Bleu-1 was 67.1, bleu-2 was 45.1, bleu-3 was 29.9 and bleu-4 was 21.1. Experiments were carried out on the database flickr30k by designing the algorithm. Bleu-1 was 72.3, bleu-2 was 51.8, bleu-3 was 37.1 and bleu-4 was 25.1. From the comparison results of the simulations of unmanned vehicles with or without a system, it can provide effective safety guarantee for unmanned driving.

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Section: Introductionmentioning

confidence: 99%

Study on a risk model for prediction and avoidance of unmanned environmental hazard

Qiu

Zhang

et al. 2022

Sci Rep

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“…The composition of onboard computing resources of MR usually containing some individual computing devices [3][4][5][6], and distribution strategy of functions of ICS for these devices significantly affect on special aspects of realization these ICS.…”

Section: Introductionmentioning

confidence: 99%

The Universal Onboard Information-control System for Mobile Robots

Filaretov

Yukhimets

Mursalimov

2015

Procedia Engineering

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The approach to creation of universal software platform for realization of information-control system of mobile robot is proposed in this work. The main feature of this platform is universal structure of software components which consist of functional part and communication part. This structure allows provide the independence of functional part from hardware of mobile robot. The minimal set of software components which allows create the core of information-control system of mobile robot is proposed. Also the algorithms realizing of functions of these components are described.

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Quadcopter Modeling in Virtual Reality for Dynamic Visualization

Kuantama

Ţarcă

2018

2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)

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JOMS:System Architecture for Telemetry and Visualization on Unmanned Vehicle

Cited by 3 publications

References 6 publications

Study on a risk model for prediction and avoidance of unmanned environmental hazard

Study on a risk model for prediction and avoidance of unmanned environmental hazard

The Universal Onboard Information-control System for Mobile Robots

Quadcopter Modeling in Virtual Reality for Dynamic Visualization

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