Sense → Estimate → Adapt → Decide → Act
SafeSense 3D is a simulation-first safety architecture for automated machinery that dynamically determines the required protective envelope based on machine motion, hazard proximity, and sensor confidence.
Developed for National Student Hack-A-Stage 2026 — Track 01: Algorithmic Safety & Hazard Mitigation in Automated Systems. Team: Robo Rebels
Automated machinery commonly relies on predefined safety zones and threshold-based responses. A fixed safety zone does not account for:
- Machine velocity
- Stopping distance
- Reaction delay
- Sensor uncertainty
- Occlusion
- Conflicting sensor observations
The core question: how much safety space does the machine need right now?
SafeSense answers this continuously by combining machine dynamics with sensor confidence, following a five-stage pipeline:
- Sense — virtual LiDAR + thermal observation
- Estimate — distance, velocity, and confidence
- Adapt — stopping distance + uncertainty margin
- Decide — risk classification via TTC
- Act — slow / brake / E-stop
Safety principle: uncertainty can expand the protective envelope, but it can never reduce the deterministic safety floor.
d_safe = d_stop + d_reaction + d_uncertainty
d_stop = v² / (2a)— required stopping distanced_reaction = v × t_delay— sensing, computation, and actuation delayd_uncertainty = f(confidence)— lower confidence increases the protective margin
Risk states are classified using distance, time-to-collision (TTC), and the adaptive safety envelope: NORMAL → WARNING → BRAKE → E-STOP.
pip install -r requirements.txt
python3 simulation/run_simulation.pyThis runs six deterministic validation scenarios and writes results to results/validation/safesense_validation.csv.
| Scenario | Confidence | Distance (m) | TTC (s) | d_safe (m) | State |
|---|---|---|---|---|---|
| Clear / high confidence | 0.95 | 2.75 | 2.75 | 1.14 | NORMAL |
| Approach / high confidence | 0.92 | 2.00 | 2.00 | 1.17 | WARNING |
| Critical approach | 0.90 | 1.30 | 1.30 | 1.18 | WARNING |
| Occlusion / low confidence | 0.55 | 1.65 | 1.27 | 1.46 | WARNING |
| Conflicting sensors | 0.35 | 1.25 | 0.89 | 1.62 | BRAKE |
| Imminent hazard | 0.85 | 0.82 | 0.59 | 1.22 | E-STOP |
Lower confidence increases the uncertainty margin and therefore expands d_safe. All values above are outputs of the deterministic simulation model, not measurements from physical sensors.
SafeSense 3D is a supervisory decision-support layer. It is not a certified industrial safety controller — certified hardwired / safety-PLC functions remain the final safety authority in any real deployment.
- Calibrate uncertainty models using real sensor data
- Validate against representative industrial robot/AGV scenarios
- Integrate with certified safety controllers under appropriate industrial standards
- Develop automated sensor-placement optimization for complex workspaces
See the LICENSE file for licensing information.