Rug
The rug acts as the primary interface, passively monitoring movement and interpreting gesture inputs like taps and swipes to manage schedules, trigger routines, and track daily tasks.
What is our project?
SHRUG is a sensor-equipped smart rug and companion robot designed to reduce the cognitive friction of everyday home routines. SHRUG embeds intelligence into your daily life using pressure, motion, and conductive sensors to detect presence, recognize users, and respond to simple foot gestures.
The system works in 2 parts.
Robot
The companion robot sits nearby and serves as the voice of the system delivering personalized responses, weather forecasts, transit alerts, and end-of-day summaries drawn from the user's existing calendar, reminders, and health apps.
Together, they create a single, ambient system that comes alive under your feet.
Value Proposition
SHRUG takes the load off your brain by removing the small but constant decisions that can slow down your morning and weigh on your evening without adding a new device to learn or a new habit to build.
See SHRUG in action
Watch our video to get a glimpse of what life could be with a smart rug and robot companion!
Why SHRUG?
SHRUG is for students and young working professionals who are navigating packed schedules, early mornings, and the constant stress of staying on top of everything.
Students and young working professionals spend the bulk of their mental energy managing daily transitions at home, outside of school or the office. Oftentimes, people have the motivation and the tools to be productive but they struggle with the decisions.
They might already be using calendars, reminders, and smart home devices but find that managing all of them adds friction rather than removing it. Here, the main problem is cognitive overload.
Who
Home
Overload
Research Methodologies
1
Contextual Inquiry
Four graduate students and four working professionals all living in apartment environments in their twenties and thirties. Observations took place in their home during key moments of their daily routines, including morning prep, meal planning, household chores, and workspace organization.
2
Diary Study
Eight participants captured daily afternoon and evening logs of their emotional state, moments of friction, and useful tools over 3 days. We vibe-coded a digital platform for participants to record their afternoon log on the go and printed physical prompts for them to answer at home in the evening.
3
Survey
Designed and deployed a survey to broaden our findings beyond 8 participants. In total, 23 people answered our survey and confirmed that the patterns we saw in the diary study weren't just individual quirks.
4
User Enactments
Five participants from our targeted population acted out seven different scenarios with a Wizard of Oz prototype. These helped us learn which interactions and interface modalities felt natural versus intrusive.
Empathy & Journey Map
Key Insights
Across all research phases, a consistent pattern emerged around cognitive overload during transition moments, especially mornings and evenings. Participants did not lack tools (calendars, reminders, apps), but rather struggled with fragmentation and decision fatigue.
Memory
Users want a system that knows them and remembers their habits.
Structure
A structured system can compensate for dips in energy and attention when maintaining daily life.
Audio
“I wish my home could have a voice-based reminder system that understands my daily goals.”
Visual
Text-heavy displays felt overwhelming. People wanted more graphical or simplified representations.
Context
People wanted their homes to understand context when supporting them.
Experience Prototyping
To evaluate the feasibility and usability of SHRUG, we developed a mid-fidelity experience prototype that simulated the system’s core interactions: gesture-based input through the rug paired with contextual voice feedback and a projector from the companion robot.
- The rug interface was simulated using pressure-based triggers mapped to simple gestures such as taps and swipes.
- The robot interaction was represented through scripted voice responses and a projector screen that delivered contextual information such as schedule reminders, weather updates, and task prompts.
- Scenario-based enactments were used to guide the user through realistic use cases, allowing them to interact with the system as they would in their own homes.
Results
The prototype yielded several key observations:
High intuitiveness of gesture-based interaction
The user was able to quickly understand and use foot-based gestures with minimal guidance. The interaction felt natural and aligned with existing movement patterns within the home.
Reduced cognitive and physical effort
Compared to interacting with phones or multiple apps, the system felt more seamless and less mentally demanding, particularly during time-sensitive transitions.
Positive reception of proactive communication
The robot’s ability to provide timely, contextual updates without explicit input was perceived as helpful in reducing the need to constantly check devices.
Need for accuracy and control
Some concerns emerged around unintended activations and the system’s ability to distinguish between deliberate and accidental gestures, and multiple residents of the house, highlighting the importance of robust sensing and filtering mechanisms.
Expectation of personalization
There was a clear need for control over the type, timing, and frequency of prompts, suggesting that personalization will be critical for long-term usability.
Key Features
Gesture-Based Interactions
Users can control the system naturally using simple foot movements. These gestures are designed to be quick and easy, so interacting with the system feels effortless even if you're sleepy and have eyes half closed.
Presence Tracking
This feature enables the rug to recognize when someone is standing on it and even distinguish between different users through a combination of pressure and motion sensors. This allows the system to personalize responses, like loading the correct schedule.
Routine Management
The rug should know the difference between a Tuesday morning and a Sunday evening. It knows when you should be leaving, when you would like to wind down, and when to stay quiet. It helps to structure your day by anticipating some needs alongside reacting to what the user does.
Contextual Awareness
The robot understands what’s happening in the environment through the rug and responds accordingly. It uses data like presence, movement, and activity patterns to interpret what the user is doing.
Proactive Communication
It will actively engage with the user when needed. Instead of requiring you to ask for information, it can offer timely suggestions or reminders. For instance, if you’re running behind schedule, the robot might notify you or suggest adjusting your tasks for the day.
Calendar Sync
Calendar syncing connects the robot directly to your schedule, ensuring that all reminders and updates are accurate and personalized. It continuously syncs with your calendar to track upcoming events, deadlines, and tasks, allowing it to provide relevant information exactly when you need it.
The Architecture
Accessibility
A key aspect of accessibility in the system is the companion robot’s dual-mode communication. It supports:
- Voice output, allowing users to receive information without needing to look at a screen
- A built-in projector, which visually displays information such as schedules, reminders, or prompts onto a nearby wall.
This combination enables the system to adapt to different user needs and contexts.
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Results & Future Steps
What We Accomplished
We created a working prototype that semi-accurately portrays the experiences and features that this product hopes to accomplish. Some features were mock-ups that displayed the functions through Particle Photon components (display screen and rug sensor) and sensors used for small-scale production.
Limitations
Assumed technology feasibility: Some sensing and contextual inference capabilities are conceptual and not fully implemented.
What We Learned
This project reinforced the importance of designing for behavioral realities rather than idealized user intent. While participants expressed strong motivation to be productive, their actual experiences revealed gaps in execution driven by cognitive overload.
The iterative process from contextual inquiry to enactments helped shift our focus from feature-based thinking to experience design, particularly around transitions as critical moments of intervention.
We also learned that ambient and passive interactions can be far more effective in certain contexts than traditional screen-based interfaces, especially within the home environment.dkfjsd
Next Steps
In 3-5 years, we hope to have developed technology that can fully implement the features used in our prototype for mass-production. With calendar syncing, pressure sensors, system syncing, and other components, the system must be built with seamless and personalized features.
For the short term goals, we could refine personalization controls to balance automation and user agency. We could also test in diverse living environments beyond apartments to understand how this system would work in other living situations.
