3 citations · 6 across the 14 of their papers we have counts for
16 papers
Learning Robot Policies from Sparse Success Signals via STL-Guided Stein Variational Policy Gradient
Hongrui Zheng, Cristian Ioan Vasile, Antonio Loquercio +1
Learning robot policies for tasks with sparse success signals is challenging when completion depends on coordinated actions, precise contact outcomes, or satisfying several conditi…
AI Coaching for Accelerating Human Skill Development with Reinforcement Learning
Wei Wang, Enlin Gu, Antonio Loquercio +2
AI copilots can substantially boost human performance through shared control, but excessive assistance can induce over-reliance and skill atrophy. This paper studies how an embodie…
Failure-Aware Iterative Learning of State-Control Invariant Sets
Ahmad Amine, Nick-Marios T. Kokolakis, Ugo Rosolia +2
In this paper, we address the problem of computing maximal state-control invariant sets for deterministic linear systems using failing trajectories. We introduce the concept of sta…
Toward Single-Step MPPI via Differentiable Predictive Control
Viet-Anh Le, Renukanandan Tumu, Rahul Mangharam
Model predictive path integral (MPPI) is a sampling-based method for solving complex model predictive control (MPC) problems, but its real-time implementation is challenged by comp…
AdaptNC: Adaptive Nonconformity Scores for Conformal Prediction under Distribution Shift
Renukanandan Tumu, Aditya Singh, Rahul Mangharam
Rigorous uncertainty quantification is essential for the safe deployment of autonomous systems in unconstrained environments. Conformal Prediction (CP) provides a distribution-free…
Multiagent Social Influence: Modeling Persuasion in Contested Social Networks
Renukanandan Tumu, Cristian Ioan Vasile, Victor Preciado +1
We present the Social Influence Game (SIG), a framework for modeling adversarial persuasion in social networks with an arbitrary number of competing players. Our goal is to provide…
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…
PoseINN: Realtime Visual-based Pose Regression and Localization with Invertible Neural Networks
Zirui Zang, Ahmad Amine, Rahul Mangharam
Estimating ego-pose from cameras is an important problem in robotics with applications ranging from mobile robotics to augmented reality. While SOTA models are becoming increasingl…
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…
Multi-Modal Conformal Prediction Regions with Simple Structures by Optimizing Convex Shape Templates
Renukanandan Tumu, Matthew Cleaveland, Rahul Mangharam +2
Conformal prediction is a statistical tool for producing prediction regions for machine learning models that are valid with high probability. A key component of conformal predictio…
AV4EV: Open-Source Modular Autonomous Electric Vehicle Platform for Making Mobility Research Accessible
Zhijie Qiao, Mingyan Zhou, Zhijun Zhuang +10
When academic researchers develop and validate autonomous driving algorithms, there is a challenge in balancing high-performance capabilities with the cost and complexity of the ve…
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…
MOBILITY21: Strategic Investments for Transportation Infrastructure & Technology
Rahul Mangharam, Megan Reyerson, Steve Viscelli +6
America's transportation infrastructure is the backbone of our economy. A strong infrastructure means a strong America - an America that competes globally, supports local and regio…