290 citations · 687 across the 20 of their papers we have counts for
9 papers · 1 filter
Hierarchical Meta-learning-based Adaptive Controller
Fengze Xie, Guanya Shi, Michael O'Connell +2
We study how to design learning-based adaptive controllers that enable fast and accurate online adaptation in changing environments. In these settings, learning is typically done d…
CAJun: Continuous Adaptive Jumping using a Learned Centroidal Controller
Yuxiang Yang, Guanya Shi, Xiangyun Meng +4
We present CAJun, a novel hierarchical learning and control framework that enables legged robots to jump continuously with adaptive jumping distances. CAJun consists of a high-leve…
Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds
Michael O'Connell, Guanya Shi, Xichen Shi +4
Executing safe and precise flight maneuvers in dynamic high-speed winds is important for the ongoing commoditization of uninhabited aerial vehicles (UAVs). However, because the rel…
Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditions
Michael O'Connell, Guanya Shi, Xichen Shi +1
Realtime model learning proves challenging for complex dynamical systems, such as drones flying in variable wind conditions. Machine learning technique such as deep neural networks…
Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions
Guanya Shi, Wolfgang Hönig, Xichen Shi +2
We present Neural-Swarm2, a learning-based method for motion planning and control that allows heterogeneous multirotors in a swarm to safely fly in close proximity. Such operation…
Fast Uncertainty Quantification for Deep Object Pose Estimation
Guanya Shi, Yifeng Zhu, Jonathan Tremblay +4
Deep learning-based object pose estimators are often unreliable and overconfident especially when the input image is outside the training domain, for instance, with sim2real transf…
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems
Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi +3
Learning-based control algorithms require data collection with abundant supervision for training. Safe exploration algorithms ensure the safety of this data collection process even…
Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions
Guanya Shi, Wolfgang Hönig, Yisong Yue +1
In this paper, we present Neural-Swarm, a nonlinear decentralized stable controller for close-proximity flight of multirotor swarms. Close-proximity control is challenging due to t…
Neural Lander: Stable Drone Landing Control using Learned Dynamics
Guanya Shi, Xichen Shi, Michael O'Connell +5
Precise near-ground trajectory control is difficult for multi-rotor drones, due to the complex aerodynamic effects caused by interactions between multi-rotor airflow and the enviro…