activity
20192022
most citedAn Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants

6 citations · 10 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.RO2023

A Remote Sim2real Aerial Competition: Fostering Reproducibility and Solutions' Diversity in Robotics Challenges

Spencer Teetaert, Wenda Zhao, Niu Xinyuan +21

Shared benchmark problems have historically been a fundamental driver of progress for scientific communities. In the context of academic conferences, competitions offer the opportu…

cs.RO20231 cited

AMSwarm: An Alternating Minimization Approach for Safe Motion Planning of Quadrotor Swarms in Cluttered Environments

Vivek K. Adajania, Siqi Zhou, Arun Kumar Singh +1

This paper presents a scalable online algorithm to generate safe and kinematically feasible trajectories for quadrotor swarms. Existing approaches rely on linearizing Euclidean dis…

cs.RO20223 cited

Barrier Bayesian Linear Regression: Online Learning of Control Barrier Conditions for Safety-Critical Control of Uncertain Systems

Lukas Brunke, Siqi Zhou, Angela P. Schoellig

In this work, we consider the problem of designing a safety filter for a nonlinear uncertain control system. Our goal is to augment an arbitrary controller with a safety filter suc…

cs.RO2021

Fly Out The Window: Exploiting Discrete-Time Flatness for Fast Vision-Based Multirotor Flight

Melissa Greeff, Siqi Zhou, Angela P. Schoellig

Current control design for fast vision-based flight tends to rely on high-rate, high-dimensional and perfect state estimation. This is challenging in real-world environments due to…

cs.RO2021

Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control

Jacopo Panerati, Hehui Zheng, SiQi Zhou +3

Robotic simulators are crucial for academic research and education as well as the development of safety-critical applications. Reinforcement learning environments -- simple simulat…

cs.RO2020

To Share or Not to Share? Performance Guarantees and the Asymmetric Nature of Cross-Robot Experience Transfer

Michael J. Sorocky, Siqi Zhou, Angela P. Schoellig

In the robotics literature, experience transfer has been proposed in different learning-based control frameworks to minimize the costs and risks associated with training robots. Wh…