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Animesh Singhal's Projects

fcnd-3d-controls icon fcnd-3d-controls

cascaded PID controller for drone with speed & throttle constraints; capable of handling model-errors

ros_dockers icon ros_dockers

A collection of ROS1 and ROS2 dockers with GUI capabilities.

sdc_adv_lane_finding_and_detection icon sdc_adv_lane_finding_and_detection

Advanced lane-finding algorithm using distortion correction, image rectification, color transforms, and gradient thresholding. Lane curvature and vehicle displacement identified.

sdc_behavioral_cloning icon sdc_behavioral_cloning

Convolutional neural network built and trained – for end-to-end driving in a simulator – using TensorFlow and Keras.

sdc_extended_kalman_filters icon sdc_extended_kalman_filters

Kalman filter applied – on lidar and radar measurements from the self-driving car – to track a bicycle's position and velocity.

sdc_finding_lane_lines icon sdc_finding_lane_lines

Detection of highway lane lines on a video stream. Used OpenCV image analysis techniques to identify lines, including Hough Transforms and Canny edge detection.

sdc_particle_filter_for_localization icon sdc_particle_filter_for_localization

Localization of self-driving car by applying a 2-D particle filter – using map of location, (noisy) initial GPS estimate, (noisy) sensor and control data.

sdc_path_planning icon sdc_path_planning

Safe navigation of a self-driving car around a virtual highway with other traffic. The car passes slower traffic whenever possible – driving within the speed, acceleration, and jerk limits.

sdc_pid_controller icon sdc_pid_controller

Implementation of a PID controller for keeping the car on track by appropriately adjusting the steering angle and parameter tuning.

sdc_system_integration icon sdc_system_integration

ROS nodes to implement core functionality of the autonomous vehicle system, including traffic light detection, control, and waypoint following.

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