9 papers
Do as the Romans Do: Learning Universal Behaviors from Heterogeneous Agents
Caleb Chang, Davin Win Kyi, Natasha Jaques +1
Humans often acquire new skills by observing others, since observed behaviors implicitly reveal how to act in an environment. However, observations drawn from a heterogeneous popul…
Runtime Monitoring of Perception-Based Autonomous Systems via Embedding Temporal Logic
Parv Kapoor, Abigail Hammer, Ashish Kapoor +2
Runtime monitoring of autonomous systems traditionally relies on mapping continuous sensor observations to discrete logical propositions defined over low-dimensional state variable…
Learning Probabilistic Responsibility Allocations for Multi-Agent Interactions
Isaac Remy, Caleb Chang, Karen Leung
Human behavior in interactive settings is shaped not only by individual objectives but also by shared constraints with others, such as safety. Understanding how people allocate res…
Unified Generation-Refinement Planning: Bridging Guided Flow Matching and Sampling-Based MPC for Social Navigation
Kazuki Mizuta, Karen Leung
Robust robot planning in dynamic, human-centric environments remains challenging due to multimodal uncertainty, the need for real-time adaptation, and safety requirements. Optimiza…
Safe Probabilistic Planning for Human-Robot Interaction using Conformal Risk Control
Jake Gonzales, Kazuki Mizuta, Karen Leung +1
In this paper, we present a novel probabilistic safe control framework for human-robot interaction that combines control barrier functions (CBFs) with conformal risk control to pro…
Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions
Isaac Remy, David Fridovich-Keil, Karen Leung
From autonomous driving to package delivery, ensuring safe yet efficient multi-agent interaction is challenging as the interaction dynamics are influenced by hard-to-model factors…