Every robot, every sensor, every environment is different. PILGRIMS monitors your machine's performance, diagnoses problems when they occur, and solves them — while keeping a comprehensive log of errors and fixes updated in real time.
The hardest problem in machine deployment is not perception or planning. It is the fact that every robot, every sensor, and every environment is different — and that things go wrong in ways nobody anticipated. Even state-of-the-art autonomous systems can't recover on their own — they always need a human to come to the rescue. At PILGRIMS, we believe things should be the other way around.
In 2026, even small changes in the machine's environment can lead to catastrophic mistakes. Machine has no concept of its own performance: it cannot distinguish between working correctly and working incorrectly, it just blindly executes until halt.
The result is that engineering teams become the recovery layer. They monitor, they debug, and they retune. Every deployment is a bespoke effort. The knowledge of what went wrong and how to fix it lives in people, not in the system itself.
PILGRIMS adds three capabilities that most robotic stacks lack entirely. It sits alongside your existing code — you write adapters for your sensors and models, and the framework does the rest.
Continuously evaluates whether each component in the pipeline is performing within expected bounds.
When the monitor flags degradation, the system isolates why. A confidence drop in an object detector might trace to a lighting change, a novel object, or a model that has drifted. The diagnosis determines the recovery path.
Executes the appropriate repair: recalibrate an instrument, switch to a different model, adjust a control parameter, retry with a modified approach. The robot recovers autonomously and resumes their task.
Every failure and every recovery is written to a structured log — what was detected, what caused it, what was tried, what worked. This matters for two reasons. First, your team can audit exactly what happened during any run. Second, and more importantly, this log is the training data for a system that gets better over time. Each problem solved makes the next occurrence faster to resolve, and eventually, preventable.
Anywhere a machine operates in conditions that aren't perfectly controlled — which is to say, anywhere that matters — PILGRIMS applies.
AUVs operate where human intervention is impossible and communication is unreliable. PILGRIMS enables autonomous recovery when sensors fail in the deep.
Sensor fouling, pressure-induced drift, visibility shifts, communication blackouts, marine growth on optics, acoustic interference
Drones face rapidly changing conditions that degrade perception in seconds. PILGRIMS detects sensor failures and adapts before they become mission-critical.
GPS denial, wind gusts, sensor icing, lighting changes, obstacle detection failures, compass interference, barometer drift
From arctic tundra to desert heat to orbital vacuum — PILGRIMS handles environments where sensors degrade in ways no simulator can predict.
Thermal extremes, radiation effects, dust and sand contamination, communication delays, sensor degradation, optics damage
The monitor-diagnose-solve pipeline, structured logging, and adapter SDK. Everything you need to add uncertainty-aware recovery to your robot stack.
Everything in Standard, plus the system that turns logs into intelligence. Learns from every recorded failure to make recovery faster, and eventually, to prevent problems before they occur.
Recovery speed vs. fixed-threshold approaches
Detection to resolution, on device
Changes to your existing codebase
If you run a robotics operation where failures are expensive and recovery is manual, we want to build with you. You give us access to your failure data and sensors — we give you:
Or write to us directly: hello@usepilgrims.com
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