25 citations · 26 across the 5 of their papers we have counts for
8 papers
Safety Assurances for Human-Robot Interaction via Confidence-aware Game-theoretic Human Models
Ran Tian, Liting Sun, Andrea Bajcsy +2
An outstanding challenge with safety methods for human-robot interaction is reducing their conservatism while maintaining robustness to variations in human behavior. In this work,…
Physical Interaction as Communication: Learning Robot Objectives Online from Human Corrections
Dylan P. Losey, Andrea Bajcsy, Marcia K. O'Malley +1
When a robot performs a task next to a human, physical interaction is inevitable: the human might push, pull, twist, or guide the robot. The state-of-the-art treats these interacti…
Analyzing Human Models that Adapt Online
Andrea Bajcsy, Anand Siththaranjan, Claire J. Tomlin +1
Predictive human models often need to adapt their parameters online from human data. This raises previously ignored safety-related questions for robots relying on these models such…
Quantifying Hypothesis Space Misspecification in Learning from Human-Robot Demonstrations and Physical Corrections
Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac +2
Human input has enabled autonomous systems to improve their capabilities and achieve complex behaviors that are otherwise challenging to generate automatically. Recent work focuses…
A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning
Somil Bansal, Andrea Bajcsy, Ellis Ratner +2
Real-world autonomous systems often employ probabilistic predictive models of human behavior during planning to reason about their future motion. Since accurately modeling human be…
A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance
Andrea Bajcsy, Sylvia L. Herbert, David Fridovich-Keil +4
Robust motion planning is a well-studied problem in the robotics literature, yet current algorithms struggle to operate scalably and safely in the presence of other moving agents,…