2 citations · 2 across the 5 of their papers we have counts for
6 papers
From Refusal to Recovery: A Control-Theoretic Approach to Generative AI Guardrails
Ravi Pandya, Madison Bland, Duy P. Nguyen +3
Generative AI systems are increasingly assisting and acting on behalf of end users in practical settings, from digital shopping assistants to next-generation autonomous cars. In th…
Control Invariant Sets for Neural Network Dynamical Systems and Recursive Feasibility in Model Predictive Control
Xiao Li, Tianhao Wei, Changliu Liu +2
Neural networks are powerful tools for data-driven modeling of complex dynamical systems, enhancing predictive capability for control applications. However, their inherent nonlinea…
Robots that Learn to Safely Influence via Prediction-Informed Reach-Avoid Dynamic Games
Ravi Pandya, Changliu Liu, Andrea Bajcsy
Robots can influence people to accomplish their tasks more efficiently: autonomous cars can inch forward at an intersection to pass through, and tabletop manipulators can go for an…
Multi-Agent Strategy Explanations for Human-Robot Collaboration
Ravi Pandya, Michelle Zhao, Changliu Liu +2
As robots are deployed in human spaces, it is important that they are able to coordinate their actions with the people around them. Part of such coordination involves ensuring that…
Multimodal Safe Control for Human-Robot Interaction
Ravi Pandya, Tianhao Wei, Changliu Liu
Generating safe behaviors for autonomous systems is important as they continue to be deployed in the real world, especially around people. In this work, we focus on developing a no…
Towards Proactive Safe Human-Robot Collaborations via Data-Efficient Conditional Behavior Prediction
Ravi Pandya, Zhuoyuan Wang, Yorie Nakahira +1
We focus on the problem of how we can enable a robot to collaborate seamlessly with a human partner, specifically in scenarios where preexisting data is sparse. Much prior work in…