Designed an algorithm for determining the indoor position of an autonomous vehicle by populating the open-source ORB-SLAM with predefined Landmarks to get real world positioning using CUDA platform.
Ran RTAB Map using two D435 camera's with limited field of view and used the map for inventory control in the warehouse.
Designed and constructed a faster mode of Adaptive Monte Carlo Localization that can run the algorithm on
rosbag data and reproduce results for the purpose of localization improvements, automation testing etc.
Integrated Cartographer in the codebase to use landmarks for auto stitching occupancy maps of the
Designed a localization system that provided a modular codebase to have one source of truth about robot’s
state and added flexibility to support multiple devices and configurations.
Developed a feature that adds ability for robot to switch floors in a multi level warehouse.
Handled responsibilities for design and development of robot’s behavioral framework for navigation
particularly to integrate a new planner, move base flex, add faults, charging behavior etc.
Developed a feature for vacuum robot to navigate to a targeted zone in the map for cleaning within the zone
Research and Development
Designed a feature for robot to retain localization after reboot including recovery behavior using Iterative
Closest Point algorithm.
Designed an algorithm for creating an indoor floor map using PiCamera.