Projects

• Implementation of Classical Computer Vision techniques used in the front-end of visual odometry using a stereo camera setup

• Tested results on KITTI stereo vision dataset for Autonomous driving

• Used SIFT keypoints with FLANN matcher for detecting keypoints and LK optical flow to track matched keypoints

• Used 3D-2D triangulation of matched features to compute relative pose

GitHub Link | Project Report

Research Project at Perception and Autonomous Robotics Group, WPI under the guidance of Prof Nitin J Sanket

• Studying the state-of-the-art implementations on depth, pose and optical flow estimation from the motion of Monocular camera in static scenes

• Studying the impact of Uncertainty in the prediction of these parameters and how we can model it to improve predictions

GitHub Link

• Simultaneously reconstructed 3D scene and extracted camera pose from given camera correspondences 

• Implementated Classical Computer Vision pipeline using (Non) Linear triangulation and (Non) Linear PnP pipeline of matched feature correspondences

GitHub Link

• Implementation of Deep Reinforcement Learning Algorithms (DQN, PPO, A3C and DDPG) for racetrack environment in OpenAI Gym

• Tasks involved were lane keeping and overtaking

• Compared the algorithms to observe the training time and accuracy based on collision rate and lane keeping 

GitHub Link

• Utilized the KITTI LiDAR dataset to obtain Spherical projection images of the point cloud

• Implemented RangeNet architecture to predict semantic class labels

• Trained two modified networks with a Pixel Shuffling layer and one with a temporal connection between encoders to improve performance

• Obtained a 17mins/epoch reduction in training time, but there was a 5-7% drop in the mean IoU score for the classes

GitHub Link | Project Report

• Implemented autonomous navigation with dynamic obstacle avoidance using Lattice Planner (global) and Timed Path Follower (local) in hospital simulation environment

• Simulation involved humans and static hospital environment in Unity - ROS integrated framework

• Achieved smoother trajectories and better social navigation as compared to the baseline implementation using Base Global Planner and TEB Local Planner

GitHub Link | Project Report

• Generated quintic trajectories for given translational coordinates/waypoints.

• Designed a boundary layer based Sliding Mode Controller as control strategy to ensure accurate Trajectory Tracking.

• Created ROS package to simulate the trajectory tracking in Gazebo environment.

Project Report

Research Project under the guidance of Prof Berk Calli, WPI

• Studied and implemented geometric methods to detect correct grasp for daily objects from the Cornell Dataset

• Implemented a pipeline based on Elliptical Fourier Descriptors to detect object boundary and grasp axis

• Create a SCARA robot definition file with forward and inverse kinematic nodes (publisher-subscriber and service-client)

• Use ros_control package to include Joint Position Controllers, and tune the PD gains for smooth performance

• Implemented Joint Velocity Control, to track a straight line trajectory in the cartesian space, by using the Jacobian matrix

GitHub Link

• Implemented a ROS Noetic package that spawns a robot with a revolute-revolute joint configuration and an object with certain coloured features

• The goal of the node is to move the Robot in the cartesian space, so that we observe the object move from one known location to another in the image space

GitHub Link