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Shadow Removal in Off-Road Terrain Perception with Multi-Sensor Signal Processing Engineering and Innovative Technology Development (EITD), Un
- Format:
- Book
- Conference/Event
- Author/Creator:
- Gardner, S. D., author.
- Conference Name:
- 2024 NDIA Michigan Chapter Ground Vehicle Systems Engineering and Technology Symposium (2024-08-13 : Novi, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2024
- Summary:
- Autonomous vehicle navigation requires signal processing of the vehicle's sensors to provide meaningful information to the planners such that challenging artifacts like shadows, rare events, obstructive vegetation, et cetera are identified properly, avoiding ill-informed navigation. Using a single algorithm such as semantic segmentation of camera images is often not enough to identify those challenging features but can be overcome by processing more than one type of sensor and fusing their results. In this work, semantic segmentation of camera image and LiDAR point cloud signals is performed using Echo State Networks to overcome the challenge of shadows identified as obstructions in off-road terrains. The coordination of algorithms processing multiple sensor signals is shown to avoid unnecessary road obstructions caused by high-contrast shadows for more informed navigational planning
- Notes:
- Vendor supplied data
- Publisher Number:
- 2024-01-4073
- Access Restriction:
- Restricted for use by site license
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