ADAS

Life-saving algorithms which secure road safety with highest accuracy

Machine Vision in industrial applications

Robots working in industrial applications perform many valuable tasks: from inspection to quality control, from assembling to locating/transporting parts. These tasks need highly accurate visual feedback: the robot is conveniently equipped with a camera as needed by the application. Machine vision systems operating in the industry can be of different kinds and must find solution to different challenges.

Machine Vision for Robotics

This article explains how different types of cameras provide mechanical support to robots by helping them navigate in the real world. Besides that, robots serving in different fields of activity require different skills. As a result, you will read here the different ways by which Machine Vision algorithms power robots in the main industries and markets, each according to their desired tasks.

Object Detection Methods for Robots

Robots need to recognize objects, if we want them to perform their activity. To solve this challenge, they take advantage of object detection and classification algorithms which give them the ability to be efficient and practical in the recognition tasks. Machine learning software enable robots to detect all instances of an object. This article details the different classes of object detection methods for robots, including the most sophisticated ones, based on Convolutional Neural Networks.

Machine Vision Robots for Semiconductors

Machine vision algorithms are also used to operate robots in the high-precision semiconductor industry. Robots perform these intelligent tasks supported by machine vision software: several methods are currently used to detect defects and classify them, with important economies in both time and money. Robots in the semiconductor industry too can take advantage of deep learning techniques: their main benefit is the dramatic improvement in the defect classification abilities of the robotic devices.

Robots using Machine Vision in Agriculture

Among the many tasks performed by robots in agriculture, a large part is activated by machine vision algorithms. A very partial list of these tasks would include fields plowing, seeds planting, weeds handling, monitoring of produce growth (be it via ground-based robots or by flying robotic UAVs), fruits and vegetables picking, as well as sorting and grading of produce. This article gives a panoramic view of what our algorithms for robotics can do for your project in agriculture, including robots using Deep Learning in agriculture.