30 citations · 34 across the 6 of their papers we have counts for
8 papers · 1 filter
User-specific, Adaptable Safety Controllers Facilitate User Adoption in Human-Robot Collaboration
Ahalya Prabhakar, Aude Billard
As assistive and collaborative robots become more ubiquitous in the real-world, we need to develop interfaces and controllers that are safe for users to build trust and encourage a…
Multimodal Sensory Learning for Real-time, Adaptive Manipulation
Ahalya Prabhakar, Stanislas Furrer, Lorenzo Panchetti +2
Adaptive control for real-time manipulation requires quick estimation and prediction of object properties. While robot learning in this area primarily focuses on using vision, many…
Credit Assignment Safety Learning from Human Demonstrations
Ahalya Prabhakar, Aude Billard
A critical need in assistive robotics, such as assistive wheelchairs for navigation, is a need to learn task intent and safety guarantees through user interactions in order to ensu…
Ergodic imitation: Learning from what to do and what not to do
Aleksandra Kalinowska, Ahalya Prabhakar, Kathleen Fitzsimons +1
With growing access to versatile robotics, it is beneficial for end users to be able to teach robots tasks without needing to code a control policy. One possibility is to teach the…
Ergodic Specifications for Flexible Swarm Control: From User Commands to Persistent Adaptation
Ahalya Prabhakar, Ian Abraham, Annalisa Taylor +7
This paper presents a formulation for swarm control and high-level task planning that is dynamically responsive to user commands and adaptable to environmental changes. We design a…
An Ergodic Measure for Active Learning From Equilibrium
Ian Abraham, Ahalya Prabhakar, Todd D. Murphey
This paper develops KL-Ergodic Exploration from Equilibrium (), a method for robotic systems to integrate stability into actively generating informative measurements…