You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Developing simple algorithms for lane following and collision avoidance for safe and efficient operation of self-driving cars using depth camera sensor and deep learning methods like YOLO.
Problem details
Lane following entails accurately tracking road lanes to maintain the vehicle's position within the lane. Collision avoidance involves detecting obstacles in the vehicle's path and taking evasive actions to prevent accidents.
Experiment details
Lane detection using segmented images obtained from collected data from sensor in environment and feeding it to a DL model
Collision avoidance using depth camera(Tentatively like Intel RealSense) and object detection from DL Models.
Also prepare documentation and tutorial for easy understanding of the same
Problem description
Developing simple algorithms for lane following and collision avoidance for safe and efficient operation of self-driving cars using depth camera sensor and deep learning methods like YOLO.
Problem details
Lane following entails accurately tracking road lanes to maintain the vehicle's position within the lane. Collision avoidance involves detecting obstacles in the vehicle's path and taking evasive actions to prevent accidents.
Experiment details
#Email
[email protected]
The text was updated successfully, but these errors were encountered: