Developed an end-to-end docking location detection network based on synergy of deep point set networks and Hough voting.
Developed a real-time computer vision pipeline to find potential docking locations indoor environments for wheelchairs using point cloud data.
Real-time wheelchair navigation with shared control using model predictive path integral (MPPI) controller.
Indoor object detection using Votenet for pointclouds captured from RGB-D cameras in ROS simulation.
Image-based visual servoing in eye-in-hand configuration for Universal Robot 5 using Microsoft Kinect V2 camera.
Developed an optimal path planning algorithm in obstacle rich environments. BugFlood unlike its predecessor uses a split and kill approach to advance in the environment. Performance of this algorithm was compared with different planners from Open Motion Planning Library (OMPL) and visibility graph methods.
Developed a static analysis Clang based tool for ROS to reduce network latency and dropout rate by optimizing message size.