319 citations · 1.6k across the 72 of their papers we have counts for
9 papers · 1 filter
An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants
SiQi Zhou, Angela P. Schoellig
Deep neural networks (DNNs) have emerged as a popular mathematical tool for function approximation due to their capability of modelling highly nonlinear functions. Their applicatio…
Online Trajectory Generation with Distributed Model Predictive Control for Multi-Robot Motion Planning
Carlos E. Luis, Marijan Vukosavljev, Angela P. Schoellig
We present a distributed model predictive control (DMPC) algorithm to generate trajectories in real-time for multiple robots. We adopted the \textit{on-demand collision avoidance}…
Trajectory Tracking for Quadrotors with Attitude Control on
Dave Kooijman, Angela P. Schoellig, Duarte J. Antunes
The control of a quadrotor is typically split into two subsequent problems: finding desired accelerations to control its position, and controlling its attitude and the total thrust…
aUToTrack: A Lightweight Object Detection and Tracking System for the SAE AutoDrive Challenge
Keenan Burnett, Sepehr Samavi, Steven L. Waslander +2
The University of Toronto is one of eight teams competing in the SAE AutoDrive Challenge -- a competition to develop a self-driving car by 2020. After placing first at the Year 1 c…
The regular indefinite linear quadratic optimal control problem: stabilizable case
Marijan Vukosavljev, Angela P. Schoellig, Mireille E. Broucke
This paper addresses an open problem in the area of linear quadratic optimal control. We consider the regular, infinite-horizon, stability-modulo-a-subspace, indefinite linear quad…
Hierarchically Consistent Motion Primitives for Quadrotor Coordination
Marijan Vukosavljev, Angela P. Schoellig, Mireille E. Broucke
We present a hierarchical framework for motion planning of a large collection of agents. The proposed framework starts from low level motion primitives over a gridded workspace and…
A Modular Framework for Motion Planning using Safe-by-Design Motion Primitives
Marijan Vukosavljev, Zachary Kroeze, Angela P. Schoellig +1
We present a modular framework for solving a motion planning problem among a group of robots. The proposed framework utilizes a finite set of low level motion primitives to generat…
Knowledge Transfer Between Robots with Similar Dynamics for High-Accuracy Impromptu Trajectory Tracking
Siqi Zhou, Andriy Sarabakha, Erdal Kayacan +2
In this paper, we propose an online learning approach that enables the inverse dynamics model learned for a source robot to be transferred to a target robot (e.g., from one quadrot…
No-Regret Bayesian Optimization with Unknown Hyperparameters
Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
Bayesian optimization (BO) based on Gaussian process models is a powerful paradigm to optimize black-box functions that are expensive to evaluate. While several BO algorithms prova…