Navigation Instruments TRIZ Cases
- Machine Learning for Aircraft Formation Flight Pairing
A machine learning model predicts compatible lead and trailing aircraft segments, helping fleet planners coordinate formation flights without extended tail chases.
- Vehicle Management Automation for Alternate Airport Selection
Manual pilot entries leave alternate selection dependent on cockpit input; the VMS evaluates weather, airport, and flight data for diversion choices.
- Vehicle Navigation POI Recommendations Using Card Payment History
Card payment history helps vehicle navigation surface affiliated POIs within walking distance of the destination, reducing post-parking searches.
- Elevation-Aware Traversable Maps for Autonomous Vehicle Navigation
Elevation layers keep vertically separated drivable polygons from merging, helping autonomous vehicles avoid unnecessary navigation maneuvers.
- Sensor-Based Care Facility Maps for Ultrasound Equipment Tracking
Sensor data builds care-facility maps and tracks ultrasound machine locations, battery status, and accessories to reduce locating and deployment delays.
- Vehicle Landing Guidance With UWB Beacons for Urban Precision
UWB beacons provide centimeter-level vehicle landing guidance where satellite and compass signals lose precision amid urban interference.
- Exercise-Aware Wearable Positioning for Low-Power Tracking
Satellite positioning and dead reckoning adapt to exercise type, preserving movement accuracy when signals weaken while limiting power use.
- Takeoff Runway Intersection Monitoring with Corrected Length
The flight deck calculates runway length corrections for elevation, temperature, and gradient, then flags unsuitable takeoff intersections.
- Road Feature Detection for Accurate Lane Network Map Updates
Road construction can invalidate lane connections, so detected signs, markings, lane lines, and stop lines align maps with current roads.
- GPS Polygon Mapping for Automated Plant-Row Coordinates
GPS field-boundary mapping and optical row analysis reduce manual traversal while producing coordinates for automated vehicle operations.
- Leg-Wheel Hybrid Robot State Fusion for Slip and Obstacle Errors
Leg-wheel hybrid robots can lose state accuracy on obstacles or during slip; fused inertial and odometer data improve state determination.
- Indoor Map Facility Search With Floor Segmentation
Floor-based indoor map segmentation helps users find specific mall facilities without visual overload.
- Robot Map Construction with LiDAR-Radar Reference Point Clouds
A radar probe supplies reference point clouds to update LiDAR-derived virtual walls, filling obstacle-occluded areas without re-scanning.
- Map Quality Assessment with Gold-Source Error Feedback
Gold-source comparisons expose lane-line position errors in primary map data, while feedback and weighted points improve autonomous navigation.
- Remote POI Creation Through Gesture-Based Ray Intersection
Gesture-sensed rays let users create accurate POIs remotely, avoiding travel while threshold checks refine locations.
- Integrated Airport Map Display for ATC Ground Traffic
An integrated airport map combines aircraft positions and flight data at selected intersections, reducing ATC workload and decision time.
- Dynamic Approach Timing Display for Stable Aircraft Landings
Dynamic visual cues show when approach-stabilizing actions should occur along the flight plan, reducing crew workload during non-ideal landings.
- Adaptive Digital Assistant Voice Frequency for Clear Audio
Environmental sound analysis shifts the assistant voice away from overlapping frequency ranges, improving clarity in changing surroundings.
- Procedural Mock Map Data for Exhaustive Style Validation
Procedural generation combines map attributes and spatial layouts to validate every style combination without manual data editing.
- Aircraft Crew Alert Prioritization by Operational Phase
Operational-phase contextualization dynamically ranks aircraft crew alerts so critical events stand out without manual prioritization.
- POI Entity Matching With Spatial Context Scoring
Coordinate distance and local label context combine in composite POI scores to align inconsistent datasets while reducing candidate comparisons.