Optimizing an Autonomous Robot’s Path to Increase Movement Speed
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| Publicado en: | Electronics vol. 13, no. 10 (2024), p. 1892 |
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| Autor principal: | |
| Otros Autores: | , , , |
| Publicado: |
MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 045 | 2 | |b d20240101 |b d20241231 | |
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| 100 | 1 | |a Gorgoteanu, Damian |u Center of Excellence in Robotics and Autonomous Systems—CERAS, “Ferdinand I” Military Technical Academy, 050141 Bucharest, Romania; <email>damian.gorgoteanu@mta.ro</email> (D.G.); <email>cristian.molder@mta.ro</email> (C.M.); <email>gabriel.popescu@mta.ro</email> (V.-G.P.); <email>lucian.grigore@mta.ro</email> (L.Ș.G.) | |
| 245 | 1 | |a Optimizing an Autonomous Robot’s Path to Increase Movement Speed | |
| 260 | |b MDPI AG |c 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The goal of this study is to address the challenges associated with identifying and planning a mobile land robot’s path to optimize its speed in a stationary environment. Our focus was on devising routes that navigate around obstacles in various spatial arrangements. To achieve this, we employed MATLAB R2023b for trajectory simulation and optimization. On-board data processing was conducted, while obstacle detection relied on the omnidirectional video processing system integrated into the robot. Odometry was facilitated by engine encoders and optical flow sensors. Additionally, an external video system was utilized to verify the experimental data pertaining to the robot’s movement. Last but not least, the algorithms and hardware equipment used enabled the robot to go along the path at greater speeds. Limiting the amount of time and energy required to travel allowed us to avoid obstacles. | |
| 653 | |a Data processing | ||
| 653 | |a Video | ||
| 653 | |a Optical flow (image analysis) | ||
| 653 | |a Robot dynamics | ||
| 653 | |a Planning | ||
| 653 | |a Optimization | ||
| 653 | |a Sensors | ||
| 653 | |a Robots | ||
| 653 | |a Mapping | ||
| 653 | |a Onboard data processing | ||
| 653 | |a Algorithms | ||
| 653 | |a Localization | ||
| 653 | |a Communications systems | ||
| 653 | |a Image processing | ||
| 653 | |a Obstacle avoidance | ||
| 653 | |a Cognition & reasoning | ||
| 653 | |a Semantics | ||
| 700 | 1 | |a Molder, Cristian |u Center of Excellence in Robotics and Autonomous Systems—CERAS, “Ferdinand I” Military Technical Academy, 050141 Bucharest, Romania; <email>damian.gorgoteanu@mta.ro</email> (D.G.); <email>cristian.molder@mta.ro</email> (C.M.); <email>gabriel.popescu@mta.ro</email> (V.-G.P.); <email>lucian.grigore@mta.ro</email> (L.Ș.G.) | |
| 700 | 1 | |a Vlad-Gabriel Popescu |u Center of Excellence in Robotics and Autonomous Systems—CERAS, “Ferdinand I” Military Technical Academy, 050141 Bucharest, Romania; <email>damian.gorgoteanu@mta.ro</email> (D.G.); <email>cristian.molder@mta.ro</email> (C.M.); <email>gabriel.popescu@mta.ro</email> (V.-G.P.); <email>lucian.grigore@mta.ro</email> (L.Ș.G.) | |
| 700 | 1 | |a Grigore, Lucian Ștefăniță |u Center of Excellence in Robotics and Autonomous Systems—CERAS, “Ferdinand I” Military Technical Academy, 050141 Bucharest, Romania; <email>damian.gorgoteanu@mta.ro</email> (D.G.); <email>cristian.molder@mta.ro</email> (C.M.); <email>gabriel.popescu@mta.ro</email> (V.-G.P.); <email>lucian.grigore@mta.ro</email> (L.Ș.G.) | |
| 700 | 1 | |a Ionica Oncioiu |u Department of Informatics, Faculty of Informatics, Titu Maiorescu University, 040051 Bucharest, Romania | |
| 773 | 0 | |t Electronics |g vol. 13, no. 10 (2024), p. 1892 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3059438751/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3059438751/fulltextwithgraphics/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3059438751/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |