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Jennifer Grannen

11 accepted papers

2026

Will People Enjoy a Robot Trainer? a Case Study with Snoopie the Pacerbot

ICRA 2026poster

The physicality of exercise makes the role of athletic trainers unique. Their physical presence allows them to guide a student through a motion, demonstrate an exercise, and give intuitive feedback. Robot quadrupeds are also embodied agents with robust agility and athleticism. In our work, we invest…

2025

ProVox: Personalization and Proactive Planning for Situated Human-Robot Collaboration

RA-L 2025

Collaborative robots must quickly adapt to their partner's intent and preferences to proactively identify helpful actions. This is especially true in situated settings where human partners can continually teach robots new high-level behaviors, visual concepts, and physical skills (e.g., through demo

Cited by 4SourceScholar
2024

Vocal Sandbox: Continual Learning and Adaptation for Situated Human-Robot Collaboration

CoRL 2024poster

We introduce Vocal Sandbox, a framework for enabling seamless human-robot collaboration in situated environments. Systems in our framework are characterized by their ability to *adapt and continually learn* at multiple levels of abstraction from diverse teaching modalities such as spoken dialogue, o…

Cited by 0SourcecodeScholar
2023

In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing

ICRA 2023poster

Assistance during eating is essential for those with severe mobility issues or eating risks. However, dependence on traditional human caregivers is linked to malnutrition, weight loss, and low self-esteem. For those who require eating assistance, a semi-autonomous robotic platform can provide indepe…

Cited by 13SourceScholar
2021

Disentangling Dense Multi-Cable Knots

IROS 2021poster

Disentangling two or more cables often requires many steps to remove crossings between and within cables. We formalize the problem of disentangling multiple cables and present an algorithm, Iterative Reduction Of Non-planar Multiple cAble kNots (IRON-MAN), that outputs robot actions to remove crossi…

Cited by 26SourceScholar
2021

Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics

ICRA 2021poster

Robotic fabric manipulation is challenging due to the infinite dimensional configuration space, self-occlusion, and complex dynamics of fabrics. There has been significant prior work on learning policies for specific fabric manipulation tasks, but comparatively less focus on algorithms which can per…

Cited by 84SourceScholar
2020

Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data

ICRA 2020poster

Robotic manipulation of deformable 1D objects such as ropes, cables, and hoses is challenging due to the lack of high-fidelity analytic models and large configuration spaces. Furthermore, learning end-to-end manipulation policies directly from images and physical interaction requires significant tim…

Cited by 149SourceScholar
2020

Untangling Dense Knots by Learning Task-Relevant Keypoints

CoRL 2020

Untangling ropes, wires, and cables is a challenging task for robots due to the high-dimensional configuration space, visual homogeneity, self-occlusions, and complex dynamics. We consider dense (tight) knots that lack space between self-intersections and present an iterative approach that uses lear