9 citations · 12 across the 14 of their papers we have counts for
14 papers
TacStyle: Personalizing Tactile Robot Policies using Structured Behavior Representations
Kevin Robledo, Matías I. Torres Galaz, Kumar Dixhant Rai +3
Robotic systems that assist humans should be capable of adapting their behaviors to individual user preferences. For instance, users may want a robot arm to adjust the amount of fo…
Towards Balanced Behavior Cloning from Imbalanced Datasets
Sagar Parekh, Heramb Nemlekar, Dylan P. Losey
Robots should be able to learn complex behaviors from human demonstrations. In practice, these human-provided datasets are inevitably imbalanced: i.e., the human demonstrates some…
L2D2: Robot Learning from 2D Drawings
Shaunak A. Mehta, Heramb Nemlekar, Hari Sumant +1
Robots should learn new tasks from humans. But how do humans convey what they want the robot to do? Existing methods largely rely on humans physically guiding the robot arm through…
CIVIL: Causal and Intuitive Visual Imitation Learning
Yinlong Dai, Robert Ramirez Sanchez, Ryan Jeronimus +4
Today's robots attempt to learn new tasks by imitating human examples. These robots watch the human complete the task, and then try to match the actions taken by the human expert.…
Kiri-Spoon: A Kirigami Utensil for Robot-Assisted Feeding
Maya Keely, Brandon Franco, Casey Grothoff +4
For millions of adults with mobility limitations, eating meals is a daily challenge. A variety of robotic systems have been developed to address this societal need. Unfortunately,…
RECON: Reducing Causal Confusion with Human-Placed Markers
Robert Ramirez Sanchez, Heramb Nemlekar, Shahabedin Sagheb +2
Imitation learning enables robots to learn new tasks from human examples. One fundamental limitation while learning from humans is causal confusion. Causal confusion occurs when th…
PECAN: Personalizing Robot Behaviors through a Learned Canonical Space
Heramb Nemlekar, Robert Ramirez Sanchez, Dylan P. Losey
Robots should personalize how they perform tasks to match the needs of individual human users. Today's robot achieve this personalization by asking for the human's feedback in the…
Kiri-Spoon: A Soft Shape-Changing Utensil for Robot-Assisted Feeding
Maya N. Keely, Heramb Nemlekar, Dylan P. Losey
Assistive robot arms have the potential to help disabled or elderly adults eat everyday meals without relying on a caregiver. To provide meaningful assistance, these robots must re…
Personalizing Interfaces to Humans with User-Friendly Priors
Benjamin A. Christie, Heramb Nemlekar, Dylan P. Losey
Robots often need to convey information to human users. For example, robots can leverage visual, auditory, and haptic interfaces to display their intent or express their internal s…
Surrogate Assisted Generation of Human-Robot Interaction Scenarios
Varun Bhatt, Heramb Nemlekar, Matthew C. Fontaine +4
As human-robot interaction (HRI) systems advance, so does the difficulty of evaluating and understanding the strengths and limitations of these systems in different environments an…
Towards Transferring Human Preferences from Canonical to Actual Assembly Tasks
Heramb Nemlekar, Runyu Guan, Guanyang Luo +2
To assist human users according to their individual preference in assembly tasks, robots typically require user demonstrations in the given task. However, providing demonstrations…
Robotic Lime Picking by Considering Leaves as Permeable Obstacles
Heramb Nemlekar, Ziang Liu, Suraj Kothawade +3
The problem of robotic lime picking is challenging; lime plants have dense foliage which makes it difficult for a robotic arm to grasp a lime without coming in contact with leaves.…
Two-Stage Clustering of Human Preferences for Action Prediction in Assembly Tasks
Heramb Nemlekar, Jignesh Modi, Satyandra K. Gupta +1
To effectively assist human workers in assembly tasks a robot must proactively offer support by inferring their preferences in sequencing the task actions. Previous work has focuse…
Fair Contextual Multi-Armed Bandits: Theory and Experiments
Yifang Chen, Alex Cuellar, Haipeng Luo +3
When an AI system interacts with multiple users, it frequently needs to make allocation decisions. For instance, a virtual agent decides whom to pay attention to in a group setting…