activity
20192022
most citedLearning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates

48 citations · 64 across the 9 of their papers we have counts for

collaborators

12 papers

cs.RO2022

Robust Disturbance Rejection for Robotic Bipedal Walking: System-Level-Synthesis with Step-to-step Dynamics Approximation

Xiaobin Xiong, Yuxiao Chen, Aaron Ames

We present a stepping stabilization control that addresses external push disturbances on bipedal walking robots. The stepping control is synthesized based on the step-to-step (S2S)…

eess.SY2022

Onboard Safety Guarantees for Racing Drones: High-speed Geofencing with Control Barrier Functions

Andrew Singletary, Aiden Swann, Yuxiao Chen +1

This paper details the theory and implementation behind practically ensuring safety of remotely piloted racing drones. We demonstrate robust and practical safety guarantees on a 7"…

cs.MA202148 cited

Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates

Zengyi Qin, Kaiqing Zhang, Yuxiao Chen +2

We study the multi-agent safe control problem where agents should avoid collisions to static obstacles and collisions with each other while reaching their goals. Our core idea is t…

cs.RO20207 cited

Reactive motion planning with probabilistic safety guarantees

Yuxiao Chen, Ugo Rosolia, Chuchu Fan +2

Motion planning in environments with multiple agents is critical to many important autonomous applications such as autonomous vehicles and assistive robots. This paper considers th…

cs.RO2020

Lidar-based exploration and discretization for mobile robot planning

Yuxiao Chen, Andrew Singletary, Aaron D. Ames

In robotic applications, the control, and actuation deal with a continuous description of the system and environment, while high-level planning usually works with a discrete descri…

cs.RO20204 cited

Decentralized Task and Path Planning for Multi-Robot Systems

Yuxiao Chen, Ugo Rosolia, Aaron D. Ames

We consider a multi-robot system with a team of collaborative robots and multiple tasks that emerges over time. We propose a fully decentralized task and path planning (DTPP) frame…