PaintPath: Defining Path Directionality in Maps for Autonomous Ground Vehicles
| Autor: | David Haddon, Tobias Low, Paulo Vinicius Koerich Borges, Riley Bowyer, Tirthankar Bandyopadhyay, Thomas Lowe |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Orientation (computer vision) 02 engineering and technology 020901 industrial engineering & automation Path (graph theory) 0202 electrical engineering electronic engineering information engineering Trajectory Robot 020201 artificial intelligence & image processing Point (geometry) Computer vision Artificial intelligence Motion planning business |
| Zdroj: | IROS |
| Popis: | Directionality in path planning is essential for efficient autonomous navigation in a number of real-world environments. In many map-based navigation scenarios, the viable path from a given point A to point B is not the same as the viable path from B to A. We present a method that automatically incorporates preferred navigation directionality into a path planning costmap. This ‘preference’ is represented by coloured paths in the costmap. The colourisation is obtained based on an analysis of the driving trajectory generated by the robot as it navigates through the environment. Hence, our method augments this driving trajectory by intelligently colouring it according to the orientation of the robot during the run. Creating an analogy between the vehicle orientation angle and the hue angle in the Hue-Saturation-Value colour space, the method uses the hue, saturation and value components to encode the direction, directionality and scalar cost, respectively, into a costmap image. We describe a costing function to be used by the A* algorithm to incorporate this information to plan direction-aware vehicle paths. Our experiments with LiDAR-based localisation and autonomous driving in real environments illustrate the applicability of the method. |
| Databáze: | OpenAIRE |
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