Developed a full-autonomy software stack for a F1/10 scaled autonomous racecar in ROS framework. Inclued autonomy modules- time-to-collision based automatic emergency braking, follow-the-gap reactive method, point-to-line metric based iterative-closest-point algorithm for scan-matching, A* and RRT* path-planner, April-tag based pose prediction, raceline optimization, trajectory tracking using Pure Pursuit and Model Predictive Control.
Implemented a hierarchical control strategy to compete in a virtual head-to-head racing of 1/10th scale autonomous cars. The controller employs a two-level structure- a high-level planner that generates a reference trajectory that maximizes the progress on the track ensuring obstacle avoidance. Next, we use MPC based tracker for tracking the reference trajectory obtained from the planner. The resulting strategy, capable of completing overtakes, successfully completed the race with a winning rate of 90%.
A Particle Filter based approach for real-time object tracking using mobile robots with an RGB-D camera. The particle filter estimates the location of the object in the global frame and updates the weight of the particles by computing correlation using the 2D feature descriptors of the object inside the bounding box detection. The bounding box detection was obtained using the MobileNet-SSD detection framework.
Implemented an Occupancy grid-based SLAM algorithm to generate the map of an indoor environment. Particle filters were used for localization of the robot, using measurements as scan from LIDAR, odometry data and the estimated map in the previous step.
Implemented an Unscented Kalman Filter to estimate the orientation of a rigid body using measurements from a 6 DOF IMU. UKF used the quaternion representation of the orientation to avoid singularity problems.
Created a Python API to stitch multiple images with overlapping field of views to create a panaromic effect employing Harris Corner Detector, Adaptive Non-Maximal Suppression, Histogram of Oriented Gradients feature descriptors, outlier rejection and homography estimation using RANSAC algorithm.