10 papers
Embodiment-conditioned Generalist Control for Multirotor Aerial Robots
Orestis Konstantaropoulos, Welf Rehberg, Mihir Kulkarni +1
We present a generalist position control policy capable of controlling arbitrary multirotor configurations of a certain rotor count (e.g., hexarotors or quadrotors) with a single s…
The Unified Autonomy Stack: Toward a Blueprint for Generalizable Robot Autonomy
Mihir Dharmadhikari, Nikhil Khedekar, Mihir Kulkarni +7
We introduce and open-source the Unified Autonomy Stack, a system-level solution that enables resilient autonomy across diverse aerial and ground robot morphologies. The architectu…
Efficient Knowledge Transfer for Jump-Starting Control Policy Learning of Multirotors through Physics-Aware Neural Architectures
Welf Rehberg, Mihir Kulkarni, Philipp Weiss +1
Efficiently training control policies for robots is a major challenge that can greatly benefit from utilizing knowledge gained from training similar systems through cross-embodimen…
Reinforcement Learning for Active Perception in Autonomous Navigation
Grzegorz Malczyk, Mihir Kulkarni, Kostas Alexis
This paper addresses the challenge of active perception within autonomous navigation in complex, unknown environments. Revisiting the foundational principles of active perception,…
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…