Integration of Machine Vision and Sensors

QAWhat is machine vision and why is it so important for robots?

“Carbon emissions” simply refer to the amount of carbon dioxide (CO2) emitted. In human daily activities, carbon dioxide is emitted at all times. For example, cars burning gasoline and households using natural gas contribute to this direct emission of carbon dioxide produced by the combustion of fossil fuels.

QAHow do robots “see” a part and determine its position?

This process is typically divided into the following steps:

• Image Acquisition: One or more industrial cameras (which can be 2D or 3D cameras) capture images of the part from specific angles.

• Image Processing: Software processes the raw images, such as filtering out noise and enhancing edge contrast.

• Pattern Recognition: Algorithms (such as geometric feature-based matching) identify key features of the part, such as holes, edges, or surface textures.

• Pose Calculation: Based on these feature points, the software calculates the part’s pose (position and orientation) in three-dimensional space.

• Coordinate Transformation: Finally, the calculated pose data of the part is transformed into a coordinate system that the robot controller can understand, guiding the robot’s end effector to accurately grasp or manipulate the part.

QABesides cameras, what other important sensors do robots have?

This mainly relies on the following types of sensors:

• Force/Torque Sensors: Typically installed on the robot’s wrist or end effector, used to measure the force and torque generated during the robot’s interaction with the environment. This is crucial in applications requiring precision assembly, polishing, or human-robot collaboration. For example, when pressing a pin into a hole, the force sensor can precisely control the pressure to prevent damage to the part.

• Distance Sensors: Utilizing technologies such as lasers or ultrasonic waves to measure the distance between the robot’s end effector and objects. Commonly used for obstacle avoidance, collision prevention, or precise stopping during high-speed movements.

• Tactile Sensors: Mimicking human skin, capable of sensing contact pressure and texture.

Conclusion

The integration of machine vision and sensors transforms robots from mere “mechanical hands” that can only execute preset instructions into “intelligent partners” capable of perception, judgment, and adaptation. They are key technologies for achieving high flexibility, high automation, and high intelligent manufacturing. It is these technologies that enable robots to perceive their environment, recognize objects, and adapt to changes, allowing them to complete more complex and flexible tasks. They are crucial for the evolution of robots from “repetitive executors” to “intelligent partners.”

ENDBeizhun Machinery

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