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20182022
most citedLearning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates

48 citations · 81 across the 15 of their papers we have counts for

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5 papers · 1 filter

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)…

cs.RO2020★ 7 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.RO2020★ 4 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…

cs.RO2020

Data-driven Characterization of Human Interaction for Model-based Control of Powered Prostheses

Rachel Gehlhar, Yuxiao Chen, Aaron D. Ames

This paper proposes a data-driven method for powered prosthesis control that achieves stable walking without the need for additional sensors on the human. The key idea is to extrac…