6 papers
STLGame: Signal Temporal Logic Games in Adversarial Multi-Agent Systems
Shuo Yang, Hongrui Zheng, Cristian-Ioan Vasile +2
We study how to synthesize a robust and safe policy for autonomous systems under signal temporal logic (STL) tasks in adversarial settings against unknown dynamic agents. To ensure…
Conformal Off-Policy Prediction for Multi-Agent Systems
Tom Kuipers, Renukanandan Tumu, Shuo Yang +3
Off-Policy Prediction (OPP), i.e., predicting the outcomes of a target policy using only data collected under a nominal (behavioural) policy, is a paramount problem in data-driven…
Bridging the Gap between Discrete Agent Strategies in Game Theory and Continuous Motion Planning in Dynamic Environments
Hongrui Zheng, Zhijun Zhuang, Stephanie Wu +2
Generating competitive strategies and performing continuous motion planning simultaneously in an adversarial setting is a challenging problem. In addition, understanding the intent…
Learning Local Control Barrier Functions for Hybrid Systems
Shuo Yang, Yu Chen, Xiang Yin +2
Hybrid dynamical systems are ubiquitous as practical robotic applications often involve both continuous states and discrete switchings. Safety is a primary concern for hybrid robot…
Safe Control Synthesis for Hybrid Systems through Local Control Barrier Functions
Shuo Yang, Mitchell Black, Georgios Fainekos +3
Control Barrier Functions (CBF) have provided a very versatile framework for the synthesis of safe control architectures for a wide class of nonlinear dynamical systems. Typically,…
Learning Adaptive Safety for Multi-Agent Systems
Luigi Berducci, Shuo Yang, Rahul Mangharam +1
Ensuring safety in dynamic multi-agent systems is challenging due to limited information about the other agents. Control Barrier Functions (CBFs) are showing promise for safety ass…