# NRI: Adaptive Teleoperation Interfaces for In-Home Assistive Robots

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2024 · $124,021

## Abstract

Mobile manipulators that can navigate and physically interact with their environment have the potential to 
assist people with motor limitations in carrying out activities of daily living independently. Despite this 
great potential, robots that can be safely deployed in the homes of these users do not yet exist. Until 
recently one of the key reasons for this gap was the lack of available hardware platforms, but the release 
of Stretch – a new low-cost, light-weight, inherently safe, and highly capable mobile manipulator – has 
greatly reduced the barrier to in-home deployments. A second key reason is the difficulty of robust 
autonomy given the vast variations across home environment. A practical, near-term solution is to have 
robots teleoperated by the user, which is also preferred by users in the target group who want to keep 
control over the robot. However, most existing teleoperations interfaces are not accessible to users with 
motor limitations who might have restricted input. This project aims to tackle this challenge by developing 
new systems and algorithms that enable adaptive accessible teleoperation interfaces for mobile 
manipulators. The ability to adapt to the unique requirements and preferences of these users while 
enabling the safest and most efficient operation of the robot is critical to our proposed solution.
The project involves the development of an integrated system called AccessTeleopKit implanted on the 
Stretch robot platform, and shared as open-source software. New algorithms for automatically 
customizing interfaces in AccessTeleopKit based on user input ability assessment, and automating 
repetitive parts of common tasks from user demonstrations as they teleoperate the robot will be 
developed. Contributions also include conceptual frameworks to represent teleoperation interfaces as 
mappings between user inputs and robot control outputs with Finite State Machines; and the heuristically 
assessing the accessibility of a teleoperation interface for users with different abilities. Evaluation will 
involve user studies and multi-phase long-term deployments of the robots in five homes facilitated by 
occupational therapists and will contribute new empirical findings about the usability, utility, and 
acceptance of assistance robots in the home. New guidelines for occupational therapists to use 
teleoperated robots in their practice will also be created.

## Key facts

- **NIH application ID:** 10920397
- **Project number:** 5R01EB034580-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Maya Cakmak
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $124,021
- **Award type:** 5
- **Project period:** 2023-09-06 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10920397

## Citation

> US National Institutes of Health, RePORTER application 10920397, NRI: Adaptive Teleoperation Interfaces for In-Home Assistive Robots (5R01EB034580-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10920397. Licensed CC0.

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