LEIA is a non-judgmental, expressive robot companion designed to turn habit-building from a chore into a relationship. By utilizing Ambient Computing, LEIA tracks your progress through physical objects and reacts emotionally to your consistency.
Inspiration
We often view identity as a label, but psychology defines it as the sum of repeated actions. Being consistent with these repeated actions (habits) often fails because digital habit trackers have two fatal flaws:
- Self-Reporting Bias: It’s too easy to "cheat" or misrepresent data on a screen.
- Lack of Incentive: Checking a digital box feels hollow. We’ve outgrown the age of "gold stars," but we never outgrow the need for encouragement.
We wanted to create a tracker that replaces cold data with physical, emotional presence.
What it Does
LEIA is an interactive lamp that monitors your workspace to ensure you are sticking to your goals without you ever having to touch an app.
- Object-Based Tracking: You link habits to physical "anchor objects" (e.g., a water bottle for hydration, a journal for reflection).
- Computer Vision: LEIA’s integrated camera tracks when these items appear or are removed for use.
- Emotional Mirroring:
- The "Ecstatic" State: When you hit your goals, LEIA perks up with bright, warm colors and upbeat movements.
- The "Lethargic" State: If you neglect your habits, LEIA’s light dims to a melancholy blue and its head droops, prompting you to act out of empathy for your companion.
How We Built It
We approached LEIA as two integrated systems: Perception (the brain) and Expression (the body).
- Hardware: Built using the LeLamp Developer Kit, featuring flexible motors, a camera, and a programmable LED array.
- The Brain (Software): A Python backend utilizing OpenCV for custom object detection. We trained the model to recognize specific "dwell times," calculating how long an object is absent to distinguish between a sip of water and a completed workout.
- The Emotion Engine: We bridged the data to the LeLamp API, mapping completion percentages to specific servo coordinates and RGB hex codes rather than simple binary states.
Challenges We Ran Into
- Hardware Hurdles: From initial assembly to ensuring stable signal transmission between our Python logic and the lamp's motors, the physical build provided a steep learning curve.
- We had electrical and parts-based errors almost every step of the way, hindering the development of software. We persisted nonetheless, and got the bare bones idea down.
- Data Redundancy: Initially, OpenCV’s high frame rate caused the system to count a single bottle-lift multiple times. We had to implement a Time Lag Filter (cooldown period) to ensure a "daily target" stayed accurate over 24 hours.
- Software/Hardware Bridge: Establishing a seamless connection between our "Emotion Engine" and the physical limits of the lamp.
Accomplishments That We’re Proud Of
- Successful Anthropomorphism: We moved beyond "notifications" to create a device that actually triggers a human empathy response.
- Functional Ambient Computing: We successfully built a system that works entirely in the background, removing the friction of manual data entry.
- Our First Hackathon: Getting to work with LeLamp for our first hackathon and building a system that utilizes both hardware and software.
What We Learned
- Hardware Persistence: We learned that software logic is only as good as the physical body it inhabits; persisting through assembly failures was key to seeing the "brain" come to life.
- The Psychology of Habits: We gained a deeper understanding of how externalizing discipline into a physical companion can "hack" the brain’s empathy center to improve consistency.
What's Next for LEIA - LeLamp
- Personalized Detection: Allowing users to upload photos of their own unique objects (their specific yoga mat, favorite mug, or custom journal) for accurate tracking.
- Calendar Integration: Syncing with Google Calendar so LEIA knows when you're in a meeting (and stays quiet) or when it's time for a scheduled habit.
- Cross-Device Sync: Connecting multiple LEIAs so friends can support each other’s goals, and integrating with wearables to track habits like "daily steps" even when you're away from the lamp.
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