Multi-Sensor Integration Expertise
We have extensive experience integrating a vast array of sensor types – environmental, inertial (IMUs), optical, acoustic, magnetic, location (GNSS, UWB, BLE), and specialized sensors like UWB radar.
Advanced Algorithm Implementation
We design and implement state-of-the-art sensor fusion algorithms:
- Kalman Filters: Optimal estimation for linear systems with Gaussian noise, widely used for navigation and tracking.
- Complementary Filters: Combining low-frequency and high-frequency data (e.g., accelerometer + gyroscope for orientation).
- Machine Learning Approaches: Utilizing AI/ML models to learn complex sensor correlations and perform fusion for tasks like activity recognition or anomaly detection.
UWB Radar & Location Fusion
We leverage UWB not just for precise ranging but also fuse its radar data (presence, motion ) with other sensors (e.g., cameras, IMUs) for enhanced situational awareness.
Optimization for Embedded Systems
We optimize complex fusion algorithms to run efficiently on microcontrollers with limited processing power and memory, considering energy constraints.
Rigorous Calibration & Testing
We implement robust calibration procedures and thorough testing methodologies (including HIL ) to validate the accuracy and reliability of the fused output.
Context-Aware Fusion
We develop systems where the fusion logic adapts based on the detected context or operating mode.
