41 citations · 62 across the 32 of their papers we have counts for
5 papers · 1 filter
Almost-Sure Safety Guarantees of Stochastic Zero-Control Barrier Functions Do Not Hold
Oswin So, Andrew Clark, Chuchu Fan
The 2021 paper "Control barrier functions for stochastic systems" provides theorems that give almost sure safety guarantees given stochastic zero control barrier function (ZCBF). U…
Learning Safe Control for Multi-Robot Systems: Methods, Verification, and Open Challenges
Kunal Garg, Songyuan Zhang, Oswin So +2
In this survey, we review the recent advances in control design methods for robotic multi-agent systems (MAS), focussing on learning-based methods with safety considerations. We st…
How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systems
Oswin So, Zachary Serlin, Makai Mann +4
Control barrier functions (CBF) have become popular as a safety filter to guarantee the safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to cons…
Solving Stabilize-Avoid Optimal Control via Epigraph Form and Deep Reinforcement Learning
Oswin So, Chuchu Fan
Tasks for autonomous robotic systems commonly require stabilization to a desired region while maintaining safety specifications. However, solving this multi-objective problem is ch…
NashFormer: Leveraging Local Nash Equilibria for Semantically Diverse Trajectory Prediction
Justin Lidard, Oswin So, Yanxia Zhang +8
Interactions between road agents present a significant challenge in trajectory prediction, especially in cases involving multiple agents. Because existing diversity-aware predictor…