AI-Based Perception and Sensor Fusion

AI-powered robots rely on multiple sensors to perceive their surroundings. Sensor fusion combines data from different sources to create an accurate representation of the environment.

Common Sensors Used in AI Robotics:

• Vision Sensors: Cameras with AI-based object recognition enable robots to detect shapes, colors, and text.
• LiDAR (Light Detection and Ranging): Measures distances and generates 3D maps for navigation.
• IMU (Inertial Measurement Unit): Tracks acceleration, orientation, and movement for stabilization.
• Proximity Sensors: Detect obstacles and prevent collisions in real-time.

Sensor Fusion in AI Robotics:

AI algorithms integrate data from multiple sensors to enhance perception accuracy. The Kalman filter and deep learning models are commonly used for sensor fusion.