most citedAerial Gym -- Isaac Gym Simulator for Aerial Robots

7 citations · 12 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO20241 cited

Neural Control Barrier Functions for Safe Navigation

Marvin Harms, Mihir Kulkarni, Nikhil Khedekar +2

Autonomous robot navigation can be particularly demanding, especially when the surrounding environment is not known and safety of the robot is crucial. This work relates to the syn…

cs.RO2024

Maritime Vessel Tank Inspection using Aerial Robots: Experience from the field and dataset release

Mihir Dharmadhikari, Nikhil Khedekar, Paolo De Petris +3

This paper presents field results and lessons learned from the deployment of aerial robots inside ship ballast tanks. Vessel tanks including ballast tanks and cargo holds present d…

cs.RO2024

Reinforcement Learning for Collision-free Flight Exploiting Deep Collision Encoding

Mihir Kulkarni, Kostas Alexis

This work contributes a novel deep navigation policy that enables collision-free flight of aerial robots based on a modular approach exploiting deep collision encoding and reinforc…

cs.RO20244 cited

Aerial Field Robotics

Mihir Kulkarni, Brady Moon, Kostas Alexis +1

Aerial field robotics research represents the domain of study that aims to equip unmanned aerial vehicles - and as it pertains to this chapter, specifically Micro Aerial Vehicles (…

cs.RO2023

Autonomous Exploration and General Visual Inspection of Ship Ballast Water Tanks using Aerial Robots

Mihir Dharmadhikari, Paolo De Petris, Mihir Kulkarni +7

This paper presents a solution for the autonomous exploration and inspection of Ballast Water Tanks (BWTs) of marine vessels using aerial robots. Ballast tank compartments are crit…

cs.CV2023

Task-driven Compression for Collision Encoding based on Depth Images

Mihir Kulkarni, Kostas Alexis

This paper contributes a novel learning-based method for aggressive task-driven compression of depth images and their encoding as images tailored to collision prediction for roboti…