290 citations · 687 across the 20 of their papers we have counts for
7 papers · 1 filter
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…
Competitive Control with Delayed Imperfect Information
Chenkai Yu, Guanya Shi, Soon-Jo Chung +2
This paper studies the impact of imperfect information in online control with adversarial disturbances. In particular, we consider both delayed state feedback and inexact predictio…
The Power of Predictions in Online Control
Chenkai Yu, Guanya Shi, Soon-Jo Chung +2
We study the impact of predictions in online Linear Quadratic Regulator control with both stochastic and adversarial disturbances in the dynamics. In both settings, we characterize…
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…
Online Optimization with Memory and Competitive Control
Guanya Shi, Yiheng Lin, Soon-Jo Chung +2
This paper presents competitive algorithms for a novel class of online optimization problems with memory. We consider a setting where the learner seeks to minimize the sum of a hit…