Sensor Fusion in Robotics: LIDAR, Computer Vision, and Edge AI
The accuracy and efficiency of robotic automation rely on sensor fusion—the integration of multiple data sources to enhance perception and decision-making. Robots typically utilize a combination of LIDAR sensors, stereo cameras, IMUs, and ultrasonic sensors to construct a 3D representation of their surroundings.
For autonomous vehicles and drones, Kalman filters (EKF/UKF) and Particle Filters (Monte Carlo Localization) are used to merge positional data from GPS, IMUs, and odometry sensors, ensuring precise navigation even in GPS-denied environments.
Edge AI, powered by NVIDIA Jetson Xavier and Intel Movidius Neural Compute Stick, enables real-time sensor processing without relying on cloud computation, reducing latency and increasing autonomy in robotic systems. This is crucial for applications such as robotic-assisted surgery, AI-powered security drones, and automated quality control in manufacturing.