The Why:
Autonomous mobile robots (AMRs) are becoming routine in hospitals, warehouses, and office spaces. They move materials, track inventory, and help staff work more efficiently.
But one question consistently surfaces when robotics enters human spaces: how do these machines handle privacy?
At Quasi Robotics, we understand this concern. Every Model C2 robot that rolls through a workspace carries sophisticated sensors, including cameras that enable navigation, obstacle detection, and localization. But these same sensors can raise questions about surveillance, data use, and trust.
This article explores how Quasi Robotics approaches privacy and security, especially regarding video cameras, and how we’ve designed our AMRs to keep customer environments safe, compliant, and free from unnecessary data collection.
The Role of Cameras in AMRs
Most AMRs use cameras to understand their surroundings. They rely on visual cues to navigate, avoid collisions, and map spaces.
The misconception is that these cameras function like surveillance systems, recording video, storing faces, or tracking people.
In reality, for many modern systems, the process looks nothing like security footage.
Instead of saving images, AMRs extract simple data points such as lines, shapes, and contrast patterns to calculate position and movement. That information is used instantly, then deleted.
No photo albums, no cloud folders, no archives of who walked by.
Data Minimization by Design
Privacy in robotics often starts with data minimization, collecting only what is essential to perform a task.
For most AMRs, personal data is not necessary. The robots do not need to recognize employees or analyze documents; they just need spatial awareness to operate safely.
By keeping data collection this narrow, companies can deploy robots in sensitive environments like hospitals or corporate offices without risking exposure of personal information
That’s why the Model C2 does not collect, process, or store any personally identifiable information (PII). The robot has no need to recognize faces, read documents, or analyze sensitive visual content. Its navigation algorithms depend solely on spatial features that can’t be tied to people or personal
data.
This approach ensures that our AMRs can operate safely in environments where privacy is paramount, such as hospitals, office buildings, or retail spaces, without risking accidental data exposure or misuse.
Local Processing Keeps Environments Secure
A key design principle in privacy-first robotics is on-device processing.
When data, such as a camera frame, is processed locally and never uploaded to the cloud, the risk of leaks or breaches drops significantly.
This approach means that even if someone accessed the robot, there would not be any usable footage or personal data to find.
By keeping all computation within the robot itself, privacy becomes a built-in safeguard rather than an added feature. Local processing not only protects users but also improves reliability, since the robot can function without constant connectivity. This balance of security and independence is becoming the standard for modern automation systems.
What Happens to Operational Data
Privacy in the Model C2 isn’t an afterthought; it’s an architectural feature.
While robots do not store video or audio, they do collect non-personal metrics such as distance traveled, sensor readings, and battery performance.
This information helps monitor system health or predict maintenance needs.
When it is transmitted to a cloud platform, it is typically encrypted, anonymized, and used only for technical diagnostics.
Here’s how it works:
1. Image Capture: The camera captures a frame to analyze the environment.
2. Feature Extraction: Key environmental features are converted into numerical representations.
3. Localization and Mapping: The robot uses those numerical features to determine its position and plan its next move.
4. Immediate Disposal: The original image data is discarded. Nothing is stored or transmitted.
No Audio Recording or Monitoring
While some robotics platforms include microphones for remote assistance or voice control, the Model C2 does not record, process, or store audio information. If a microphone is physically present on the hardware, it remains
permanently disabled for capture or monitoring purposes. This ensures that your environment remains private and that no ambient conversations or sounds are ever collected.
Privacy Regulations and Ethical Standards
As robotics becomes more integrated into public and private spaces, manufacturers are increasingly aligning with global privacy laws such as the GDPR in Europe and the CCPA in California.
These frameworks emphasize transparency, consent, and control, principles that are starting to shape how autonomous systems are engineered.
Users can often review or request deletion of any stored data, similar to rights under consumer privacy laws.
Compliance with these regulations is not just about meeting legal standards but about reinforcing public trust in automation. When users know how their data is handled and can control it, confidence in robotic systems grows. This trust is essential for long-term adoption, helping ensure that privacy protections evolve alongside technological innovation.
Cloud Connect: When Data Leaves the Robot
For Wi-Fi-enabled units, Quasi Robotics offers Cloud Connect, a secure platform that allows limited non-personal operational data to be uploaded for diagnostics, fleet management, and predictive maintenance.
Even in this case, privacy remains fully intact. Only the following categories of non-personal data are transmitted:
– Odometry Data: Distance traveled and waypoint names (not images).
– Environmental Sensors: Temperature, humidity, and air pressure readings.
– Diagnostics: Battery health, power consumption, and sensor status.
– Charging Events: Time and details of each charging session.
No visual, audio, or location data that could identify individuals or specific environments is ever uploaded. All transmissions are encrypted and stored securely on Quasi Robotics’ servers.
The Bigger Picture
Privacy in robotics is not a one-time policy; it is a design philosophy.
The trend across the industry shows a move away from storing human-related data and toward systems that work independently of personal information.
As AMRs continue to evolve, the challenge will be balancing advanced capabilities such as smarter navigation or contextual awareness with strict data boundaries.
The goal is simple: build machines that help humans, without watching them.
The Future of Privacy in Robotics
As robotics technology advances, so will the expectations for ethical data use. We envision a future where AMRs become even more intelligent and interconnected, yet remain fundamentally private.
Future generations of Quasi Robotics products will continue to evolve with this guiding principle: robots should serve people, not watch them. We will keep refining our systems to ensure that every Quasi robot, whether in a hospital corridor or a supermarket aisle, continues to respect and protect the privacy of the environments it serves.
Final Thoughts
Privacy isn’t just a compliance checkbox, it’s a design philosophy. By ensuring that our AMRs operate without recording, storing, or transmitting visual or personal data, Quasi Robotics sets a new benchmark for responsible automation.
With the Model C2, customers gain the full benefit of cutting-edge mobility, intelligence, and reliability without ever compromising their privacy or peace of mind.
To learn more about our approach to security and privacy, visit www.quasi.ai/privacy or contact us directly at privacy@quasi.ai.