Autonomous Vehicles: Obstacle Detection
2023
- 54Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage54
- Abstract Views54
Artifact Description
The purpose of this research is to develop an algorithm for the Duckiebot to detect obstacles in the Duckietown field. Autonomous vehicles rely on internal and external sensors to understand the surrounding environment. On the road, self-driving vehicles depend on image processing to identify cars and pedestrians. Through this research, the purpose is to prevent collisions between the Duckiebot and other robots on the game field using a vision algorithm. Linux, Python, machine learning, and a camera are used to navigate the robot and detect colors and objects.
Bibliographic Details
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