We present CAJun, a novel hierarchical learning and control framework th...
Learning to control unknown nonlinear dynamical systems is a fundamental...
Representation learning based on multi-task pretraining has become a pow...
Executing safe and precise flight maneuvers in dynamic high-speed winds ...
We study a variant of online optimization in which the learner receives
...
We present an online multi-task learning approach for adaptive nonlinear...
Realtime model learning proves challenging for complex dynamical systems...
We present Neural-Swarm2, a learning-based method for motion planning an...
Deep learning-based object pose estimators are often unreliable and
over...
Learning-based control algorithms require collection of abundant supervi...
In this paper, we present Neural-Swarm, a nonlinear decentralized stable...
This paper studies online control with adversarial disturbances using to...
We study the problem of safe learning and exploration in sequential cont...
Precise trajectory control near ground is difficult for multi-rotor dron...