Overview of the subsystem:

Note: Ellipses correspond to ROS Nodes and Rectangles correspond to the corresponding topics.

Node	Build Status	Working Status	Credits	Future Work
birds_eye			-	-
classifier			IGVC IITK (Built from scratch)	Improving training model for better accuracy
gSLICr/gslicr_ros			gSLICr	Tuning Parameters
masker			IGVC IITK (Built from scratch)	-
top_view			IGVC IITK (Built from scratch)	-
zed-ros-wrapper			ZED ROS wrapper	-

This package contains the classifier_node and the launchfile for the full vision pipeline. The classifier_node takes averaged image and uses pre-trained random forrest model to predict each superpixel as lane/not lane and publishes the prediction array to rostopic /predictions. pipeline.launch is the launch file for the vision pipeline. Sequentially executes the following ros nodes :

• top_view
• gslicr_ros
• classifier
• masker

gSLICr is a GPU accelerated implementation of SLIC (Simple Linear Iterative Clustering) for real-time superpixel segmentation of images.

Modified for averaging of colors of pixels in each superpixel.

gslicr_ros is the ROS implementation of gSLICr. It subscribes to the top_view image and publishes

• averaged rgb values of superpixels on the rostopic /gslicr/averages
• superpixel id of each pixel on the rostopic /gslicr/segmentation

This package contains a node 'masker_node' that simply takes all the predictions from the classifer and all the superpixel id from gSLICr and masks the corresponding superpixels with the prediction values. It finally publishes the binary image on the rostopic /final_image.

This node takes IMU sensor data to dynamically perform inverse perspective transform to get the top view of camera images and publishes the transformed image to the rostopic /top_view.

ZED ROS wrapper lets you use the ZED stereo camera with ROS. It outputs the camera left and right images, depth map, point cloud, odometry information and supports the use of multiple ZED cameras.