Understanding the Core Concepts

Image Acquisition & Sensors

The process begins with capturing an image. Robots typically utilize cameras, often CCD (Charge-Coupled Device) or CMOS (Complementary Metal-Oxide-Semiconductor) sensors. These sensors convert light into electrical signals.

Image Processing – Pre-processing

Raw image data is noisy and requires processing. Common pre-processing steps include noise reduction (e.g., Gaussian blur), contrast adjustment, and geometric correction to account for camera distortions.

Gaussian Blur:  σ = k * |x| + k * |y| , where σ is the standard deviation of the blur kernel, k is a scaling factor, and (x, y) are pixel coordinates.

Feature Extraction & Object Recognition

Once an image is pre-processed, algorithms extract key features – lines, edges, corners, or even more complex shapes. These features are then matched against known patterns (templates) to identify objects.

Perception & Decision Making

The identified object information is fed into a perception system, which combines it with robot’s internal state and planned actions. This allows the robot to make decisions about its movement and interaction with the environment.

Frequently asked questions

Try it live

Everything above runs in your browser — open Inverse Kinematics (FABRIK) and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.