What are the latest trends and innovations in 3D vision for industrial applications?

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3D vision is a key technology for many industrial applications, such as robotics, inspection, metrology, and quality control. It enables machines to perceive depth and shape information from images, which can improve accuracy, efficiency, and safety. But how does 3D vision work, and what are the latest trends and innovations in this field? In this article, we will explore some of the main methods, challenges, and opportunities of 3D vision for industrial applications.

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Nicholas Longworth

Business and Technical Consultant for Industrial Robotics at SICK
Thomas Benninger

Von der Vision zur Realit?t: Hochmoderne L?sungen für SPS und Machine Vision.
Joerg Clement

Perspective Matters--Its not about what you see it′s about how you see it.

1 Methods of 3D vision

When capturing 3D information from images, the type of camera, light source, and algorithm used will determine the method. Stereo vision involves using two or more cameras that are aligned and calibrated to capture images from different viewpoints and compare them to find corresponding points. Structured light projects a pattern of light, such as stripes or dots, onto the object or scene and the camera captures the image of the distorted pattern which reflects the shape and depth. Time-of-flight measures the time it takes for a pulse of light, usually infrared, to travel from the camera to the object or scene and back. The time difference is then used to create a depth map.

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Nicholas Longworth

Business and Technical Consultant for Industrial Robotics at SICK
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There are many more methods of building a 3D image that structured light stereo or time of flight. Technologies such as laser triangulation, time coded structured light, active structured light stereo, and others all have their places in applications. Each technology has pros and cons that make it a better fit for one application vs another. It is also important to note that these cameras generate both a 2D image and a 3D image for processing.

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2 Challenges of 3D vision

Despite the advances in 3D vision technology, there are still some challenges and limitations that need to be addressed. Occlusion can reduce the accuracy and completeness of the 3D information, while reflections can create noise or distortion. Calibration involves adjusting the parameters and settings of the camera and the light source to ensure they are synchronized, while processing requires high computational power and memory. All of these issues can affect the quality and consistency of the 3D information.

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Pujan B.

Business Development Manager @ SinceVision | Machine Vision Solutions | Sensor Technology | Industrial Automation |
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Here are a few other challenges of 3D vision: Limited Visibility: Since 3D vision systems frequently rely on line-of-sight data, they may find it difficult to reconstruct 3D models of objects that are partially or completely obscured or to take precise measurements of them. Environmental Factors: The accuracy of 3D vision systems can be greatly impacted by unfavorable environmental conditions, such as bright illumination, dynamic lighting, or the presence of reflective surfaces. Privacy and Security Issues: As 3D vision systems can gather personal data about people without their knowledge or agreement, using them for tracking or surveillance purposes presents privacy issues.

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3 Opportunities of 3D vision

Despite the challenges, 3D vision offers many opportunities and benefits for industrial applications. It can provide more accurate and reliable information than 2D vision, which can improve the performance and productivity of robots, scanners, and sensors. Additionally, 3D vision can adapt to different environments and conditions, such as lighting, texture, and color. This increases the flexibility and versatility of machines and systems used for inspection, measurement, and sorting. Lastly, 3D vision can detect and avoid obstacles and hazards, such as collisions, falls, and injuries. This improves the safety and security of machines and systems, as well as humans and other objects.

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Joerg Clement

Perspective Matters--Its not about what you see it′s about how you see it.
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3D vision technology is reshaping industries like manufacturing, healthcare, and robotics. From elevating quality control in production to enhancing surgical precision, its impact is profound. In agriculture, retail, entertainment, construction, electronics, and security, 3D vision brings efficiency and accuracy. Its applications span autonomous navigation, inventory management, and immersive experiences in gaming and entertainment. As technology evolves, the markets for 3D vision continue to expand, unlocking new possibilities across various sectors, promising a future where machines perceive and interact with the world in three dimensions.

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Thusinthaka Thinesh Hewa Pathiranna

Embedded Engineer @ Zebra Technologies | Embedded Memory Optimization | AOSP
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Depth Sensing: Depth sensing cameras are common in industry.Cameras can measure the distance between the camera and the object for object detection. Helps in object-dimensioning and space calculation applications. Robotic Guidance: 3D vision systems are increasingly being used to guide robots in industrial settings. These systems can accurately determine the position and orientation of objects. AR: It uses 3D vision to overlay digital information onto the physical world, aiding in tasks like assembly, maintenance, and training. 3D Scanning: scanning technology has made significant advancements, enabling accurate, fast and non-contact measurements of complex shapes. This is extremely useful in industries such as automotive and aerospace.

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4 Innovations in 3D vision

In recent years, the field of 3D vision technology has seen a range of new developments and innovations, such as deep learning. Artificial neural networks can be used to learn from large datasets and carry out complex tasks such as recognition and segmentation. This can not only improve accuracy and efficiency of 3D vision algorithms and applications, but also open up the possibility of semantic understanding and scene reconstruction. Edge computing is another development which involves processing data near the source rather than sending it to a central server or cloud, reducing latency, bandwidth requirements, and increasing privacy and security. Additionally, multi-modal fusion combines different types of data like images, depth maps, audio, and sensors to create a more comprehensive representation of an object or scene. This can enhance the performance and reliability of 3D vision applications as well as enable new functionalities like gesture recognition and human-machine interaction.

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Thomas Benninger

Von der Vision zur Realit?t: Hochmoderne L?sungen für SPS und Machine Vision.
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Maybe not an innovation per se but an evolution: 3D imaging using structured light for acquisition has become extremely accurate and high resolution. This is a game-changer for applications requiring inline 3D measurements.

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5 Future of 3D vision

The future of 3D vision is promising and exciting, as the technology continues to advance. Miniaturization can reduce the size and weight of the camera and light source, while increasing the resolution and sensitivity of the sensor. This would enable 3D vision to be integrated into smaller and more portable devices, such as smartphones, drones, and wearables. Augmentation can enhance or modify reality with virtual or digital elements, creating immersive and interactive experiences like gaming, education, and entertainment. Collaboration can connect and communicate with other devices, systems, or humans using 3D vision as a medium or tool. This could facilitate cooperation and coordination, such as remote assistance, telepresence, and social networking.

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Pujan B.

Business Development Manager @ SinceVision | Machine Vision Solutions | Sensor Technology | Industrial Automation |
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More precise and dependable performance of tasks like autonomous navigation, object manipulation, and human-computer interaction will be possible for 3D vision systems as a result of improved object recognition, tracking, and categorization. 3D vision can?completely transform sectors like manufacturing, construction, and healthcare that depend on accuracy and security. 3D vision systems can help surgeons carry out less disruptive procedures with better accuracy, construction workers recognize and avoid hazards, and robots carry out complex jobs with higher precision by giving them a detailed 3D awareness of their surroundings.

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Joerg Clement

Perspective Matters--Its not about what you see it′s about how you see it.
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The future is bright! We're witnessing a continuous surge in processing power, propelled by both relentless technological advancements and the ever-evolving demands of the consumer market. This dual force, combined with innovative approaches and artificial intelligence in 3D technologies, is reshaping the narrative, systematically driving down costs and complexities associated with 3D vision solutions.

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Lee Harwood

Technical Writer at Propel Software
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3D vision will continue to advance autonomous machines with each generation, leading to improvements in areas such as path planning. 3D vision can help enable real time processing for faster, deterministic machines.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Nicholas Longworth

Business and Technical Consultant for Industrial Robotics at SICK
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Always good to talk about actual applications that are of interest to industry and not just the technology. Things like bin picking, depalletizing/palletizing and surface inspection for quality control are some examples that could be further discussed.

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What are the latest trends and innovations in 3D vision for industrial applications?

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1 Methods of 3D vision

2 Challenges of 3D vision

3 Opportunities of 3D vision

4 Innovations in 3D vision

5 Future of 3D vision

6 Here’s what else to consider

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