20 papers
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…
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…
Degradation Resilient LiDAR-Radar-Inertial Odometry
Morten Nissov, Nikhil Khedekar, Kostas Alexis
Enabling autonomous robots to operate robustly in challenging environments is necessary in a future with increased autonomy. For many autonomous systems, estimation and odometry re…
N-MPC for Deep Neural Network-Based Collision Avoidance exploiting Depth Images
Martin Jacquet, Kostas Alexis
This paper introduces a Nonlinear Model Predictive Control (N-MPC) framework exploiting a Deep Neural Network for processing onboard-captured depth images for collision avoidance i…
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…
ROAMER: Robust Offroad Autonomy using Multimodal State Estimation with Radar Velocity Integration
Morten Nissov, Shehryar Khattak, Jeffrey A. Edlund +3
Reliable offroad autonomy requires low-latency, high-accuracy state estimates of pose as well as velocity, which remain viable throughout environments with sub-optimal operating co…