12 citations · 20 across the 36 of their papers we have counts for
13 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…
Towards Quadrupedal Jumping and Walking for Dynamic Locomotion using Reinforcement Learning
Jørgen Anker Olsen, Lars Rønhaug Pettersen, Kostas Alexis
This paper presents a curriculum-based reinforcement learning framework for training precise and high-performance jumping policies for the robot `Olympus'. Separate policies are de…
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…
Collaborative Exploration with a Marsupial Ground-Aerial Robot Team through Task-Driven Map Compression
Angelos Zacharia, Mihir Dharmadhikari, Kostas Alexis
Efficient exploration of unknown environments is crucial for autonomous robots, especially in confined and large-scale scenarios with limited communication. To address this challen…
Uncertainty Aware Mapping for Vision-Based Underwater Robots
Abhimanyu Bhowmik, Mohit Singh, Madhushree Sannigrahi +2
Vision-based underwater robots can be useful in inspecting and exploring confined spaces where traditional sensors and preplanned paths cannot be followed. Sensor noise and situati…
Ariel Explores: Vision-based underwater exploration and inspection via generalist drone-level autonomy
Mohit Singh, Mihir Dharmadhikari, Kostas Alexis
This work presents a vision-based underwater exploration and inspection autonomy solution integrated into Ariel, a custom vision-driven underwater robot. Ariel carries a camera…
Semantics-aware Predictive Inspection Path Planning
Mihir Dharmadhikari, Kostas Alexis
This paper presents a novel semantics-aware inspection path planning paradigm called "Semantics-aware Predictive Planning" (SPP). Industrial environments that require the inspectio…
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…
Olympus: A Jumping Quadruped for Planetary Exploration Utilizing Reinforcement Learning for In-Flight Attitude Control
Jørgen Anker Olsen, Grzegorz Malczyk, Kostas Alexis
Exploring planetary bodies with lower gravity, such as the moon and Mars, allows legged robots to utilize jumping as an efficient form of locomotion thus giving them a valuable adv…
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.…
DeepVL: Dynamics and Inertial Measurements-based Deep Velocity Learning for Underwater Odometry
Mohit Singh, Kostas Alexis
This paper presents a learned model to predict the robot-centric velocity of an underwater robot through dynamics-aware proprioception. The method exploits a recurrent neural netwo…