An official website of the United States government
Assistive robot arms can help humans by partially automating their desired tasks. Consider an adult with motor impairments controlling an assistive robot arm to eat dinner. The robot can reduce the number of human inputs — and how precise those inputs need to be — by recognizing what the human wants (e.g., a fork) and assisting for that task (e.g., moving towards the fork). Prior research has largely focused on learning the human’s task and providing meaningful assistance. But as the robot learns and assists, we also need to ensure that the human understands the robot’s intent (e.g., does the human know the robot is reaching for a fork?). In this paper, we study the effects of communicating learned assistance from the robot back to the human operator. We do not focus on the specific interfaces used for communication. Instead, we develop experimental and theoretical models of a) how communication changes the way humans interact with assistive robot arms, and b) how robots can harness these changes to better align with the human’s intent. We first conduct online and in-person user studies where participants operate robots that provide partial assistance, and we measure how the human’s inputs change with and without communication. With communication, we find that humans are more likely to intervene when the robot incorrectly predicts their intent, and more likely to release control when the robot correctly understands their task. We then use these findings to modify an established robot learning algorithm so that the robot can correctly interpret the human’s inputs when communication is present. Our results from a second in-person user study suggest that this combination of communication and learning outperforms assistive systems that isolate either learning or communication. See videos here: https://youtu.be/BET9yuVTVU4
more »
« less
This content will become publicly available on May 9, 2026
Multi-Robot Coordination Workflows for Assistive Healthcare
Assistive robots are robots that are designed to help people with disa-bilities in their daily lives. These robots often are either too simple, and thus can-not meet the needs of the user, or are too complex, and thus become overly ex-pensive or unreliable. To mitigate this problem, we propose a system of multi-robot coordination that allows several heterogeneous robots to work coopera-tively to assist an individual. We design care task workflows that cater to the needs of a specific patient, outlining the tasks needed for the user as well as the robots that can complete each task. We then build a ROS simulation to test our coordination methods on two example workflows for PTSD care routines. Our experiments show that our coordination successfully navigates each robot to its task location at the proper time, thus showing the feasibility of these methods for multi-assistive-robot coordination.
more »
« less
- Award ID(s):
- 2150484
- PAR ID:
- 10617723
- Publisher / Repository:
- Springer International Publishing AG
- Date Published:
- Journal Name:
- Integrated design and process technology
- ISSN:
- 1090-9389
- ISBN:
- 9783031965173
- Subject(s) / Keyword(s):
- Assistive Technologies, Robots, Multi-Robot Coordination
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Nations around the world are struggling with challenges related to an increasingly aging population coupled with a growing shortage of caregivers. Intelligent, interactive systems such as robots show great promise in helping to address this care crisis. While a wealth of research exists targeting various healthcare needs, the majority of this work focuses on short-term interactions between the care recipient and the technology and do not fully consider how care robots fit into the broader scope of day-to-day life in the facility. For the long-term, sustained use of technology to support care, we need to consider how the technology fits into the broader ecosystem, considering questions such as: who is managing it? how does it alter existing workflows and routines? what extra resources (especially time) are required? Broadening technology design to encompass these ecological aspects is necessary, but it presents a rich set of challenges for robots and other intelligent systems, such as many stakeholders with different priorities and needs, safety constraints, and highly dynamic environments. Especially considering the critical role of human relationships in care, it is imperative to develop effective ways for intelligent systems to support healthcare practices rather than replace invaluable human contact. The goal of this dissertation is to help integrate robots into senior living facilities by considering how stakeholders such as caregivers and older adults can make use of autonomous robot capabilities to support their needs. To achieve this end, I present a design journey toward understanding how end-user development can support the care ecosystem and facilitate care robot integration. In this dissertation, I first present two design studies to build a case for end-user development and identify key design requirements. Building on this design work, I then present the design and evaluation of the CareAssist system an an exemplar end-user development tool that shows promise in helping to facilitate care robot integration. Overall, I do not suggest that end-user development is the only solution, and instead show that it is a critical component of the broader vision of safe, effective care robots.more » « less
-
This work proposes the development of a robot to perform appropriate tasks to assist low income older adults based on the merging of two previous studies, one which focused on task investigation and deployment of mobile robots in elder care facilities and the other on design investigation for a socially assistive robot using low-cost and modular hardware and software design. We identified that hydration, walking and socialization were tasks appropriate for the robot and most impactful to the older adults. Another outcome was the level of importance of the HRI component in the implementation of these tasks, thus merging both studies to initially investigate preferences in service robots for elder care is proposed.more » « less
-
Collaborative robots promise to transform work across many industries and promote “human-robot teaming” as a novel paradigm. However, realizing this promise requires the understanding of how existing tasks, developed for and performed by humans, can be effectively translated into tasks that robots can singularly or human-robot teams can collaboratively perform. In the interest of developing tools that facilitate this process we present Authr, an end-to-end task authoring environment that assists engineers at manufacturing facilities in translating existing manual tasks into plans applicable for human-robot teams and simulates these plans as they would be performed by the human and robot. We evaluated Authr with two user studies, which demonstrate the usability and effectiveness of Authr as an interface and the benefits of assistive task allocation methods for designing complex tasks for human-robot teams. We discuss the implications of these findings for the design of software tools for authoring human-robot collaborative plans.more » « less
-
As service robots become more capable of autonomous behaviors, it becomes increasingly important to consider how people will be able to communicate with a robot about what task it should perform and how to do the task. There has been a rise in attention to end-user development (EUD), where researchers create interfaces that enable non-roboticist end users to script tasks for autonomous robots to perform. Currently, state-of-the-art interfaces are largely constrained, often through simplified domains or restrictive end-user interaction. Motivated by our past qualitative design work exploring how to integrate a care robot in an assisted living community, we discuss challenges of EUD in this complex domain. One set of challenges stems from different user-facing representations, e.g., certain tasks may lend themselves better to a rule-based trigger-action representations, whereas other tasks may be easier to specify via a sequence of actions. The other stems from considering the needs of multiple stakeholders, e.g., caregivers and residents of the facility may all create tasks for the robot, but the robot may not be able to share information about all tasks with all residents due to privacy concerns. We present scenarios that illustrate these challenges and also discuss possible solutions.more » « less
