7 citations · 21 across the 21 of their papers we have counts for
6 papers · 1 filter
Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
NVIDIA, :, Mayank Mittal +104
We present Isaac Lab, the natural successor to Isaac Gym, which extends the paradigm of GPU-native robotics simulation into the era of large-scale multi-modal learning. Isaac Lab c…
Performance-guided Task-specific Optimization for Multirotor Design
Etor Arza, Welf Rehberg, Philipp Weiss +2
This paper introduces a methodology for task-specific design optimization of multirotor Micro Aerial Vehicles. By leveraging reinforcement learning, Bayesian optimization, and cova…
UniPilot: Enabling GPS-Denied Autonomy Across Embodiments
Mihir Kulkarni, Mihir Dharmadhikari, Nikhil Khedekar +4
This paper presents UniPilot, a compact hardware-software autonomy payload that can be integrated across diverse robot embodiments to enable autonomous operation in GPS-denied envi…
Semantically-driven Deep Reinforcement Learning for Inspection Path Planning
Grzegorz Malczyk, Mihir Kulkarni, Kostas Alexis
This paper introduces a novel semantics-aware inspection planning policy derived through deep reinforcement learning. Reflecting the fact that within autonomous informative path pl…
A Neural Network Mode for PX4 on Embedded Flight Controllers
Sindre M. Hegre, Welf Rehberg, Mihir Kulkarni +1
This paper contributes an open-sourced implementation of a neural-network based controller framework within the PX4 stack. We develop a custom module for inference on the microcont…
Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial Robots
Mihir Kulkarni, Welf Rehberg, Kostas Alexis
This paper contributes the Aerial Gym Simulator, a highly parallelized, modular framework for simulation and rendering of arbitrary multirotor platforms based on NVIDIA Isaac Gym.…