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3D Obstacle Detection
Because Field-of-View is the difference

Detect what LiDARs don’t

Detect objects above the 2D LiDAR plane

Avoid getting your robot clotheslined. 2D LiDARs do not have the ability to detect obstacles above their LiDAR plane. Inability to detect these obstacles results in risks that can be avoided with DreamVu’s 3D camera Obstacle Detection solutions – detecting obstacles as high as needed for your robot and its payload.

Detect objects below the 2D LiDAR plane

2D LiDARs detect an obstacle only if it reaches the height of the plane. Often smaller obstacles such as pallets or trash or changes in the floor plane need to be detected. While a 2D LiDAR will miss these, DreamVu’s 3D Obstacle Detection will not.

obstacle detection

Your robot with navigate and maneuver more efficiently with 3D Camera Obstacle Detection

360° horizontal Field-of-View with large vertical field-of-view improves navigation efficiency

Accurately detect different obstacle types with minimal false-positives

Seamless operation on different floor types and environments

All You Need To Know About Obstacle Detection Sensor:

Obstacle detection is the process of finding and detecting barriers in the path of a moving object. Obstruction detection systems must distinguish between obstacles and non-obstacles, as well as identify the type of obstacle. There are numerous types of obstacle detection systems, each with its own set of benefits and drawbacks.

Obstacle detection sensor has numerous applications in smart robots, intelligent cars, and autonomous agricultural vehicles. Obstacle identification based on visual picture information is one of them. Read the blog post to learn more about different types of detection systems.

Types of obstacle detection systems

Camera-based system:

A camera-based system is one of the most frequent forms of obstacle detection systems. Cameras for detection can identify a wide range of impediments, including humans, animals, and automobiles. Weather conditions, such as fog or rain, might, however, impede camera-based systems.

Sensor-based system:

A sensor-based system is another sort of obstacle detection sensor system. Sensor-based systems identify impediments using a range of sensors. Traditional sensors for detection primarily comprise laser radar sensors, visual devices, and ultrasonic sensors, infrared sensors. The underlying idea behind laser radar sensors is that distance information can be obtained by computing the time gap between laser emission and reception. Sensor-based systems are frequently more accurate than camera-based systems but can be more costly.

Advantages of Dreamvu’s obstacle-detecting method over traditional symptoms

Obstacle detection with a camera has been established as a more effective method of classifying and detecting impediments. This accuracy can be affected by various factors, including lighting effects, nighttime, bad weather, large occlusions, etc. With camera detection, estimating collision distance is also a significant difficulty. 

DreamVu’s solutions, like PAL mini, PAL, USB, and PAL ethernet, detect objects below and above the 2D LiDAR plane. You can record photographs with PAL with a 360° horizontal field of vision and a 110° vertical field of view at a quality of up to 9 megapixels, a practical depth range of 10 meters, and a minimum depth requirement. Because each frame can offer a full 3D occupancy map, PAL is the ideal sensor for autonomous mobile robot (AMR) navigation systems. PAL provides ODOA and SLAM with a full understanding of the surrounding area, allowing AMRs to localize and move along the most efficient paths.

 

The benefits of DreamVu’s solutions are

  • The combination of a 360° horizontal field of view and a wide vertical field of view improves navigation efficiency.
  • Detects several sorts of obstacles with low false positives.
  • Continuous operation on various floor types and surroundings

 

DreamVu’s vision systems, which can distinguish player motions, will certainly be deployed in the warehouse, factory floor, and so on. As a result, it is possible to view a worker loading a truck while being supported by an extended conveyor. We are redefining how machines and humans see the environment with camera-based solutions that make advantage of exceptional optics and imaging software. We are a global leader in industrial 3D sensor technology, an essential component of all automation processes.

We hope this article has helped you understand the basics of obstacle detection sensor. Contact us if you would like to learn more or discuss your specific needs with one of our experts.

Choose the solution that’s right for you

We have a configuration for all your collision avoidance needs

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Are small obstacles on the floor a problem?

Use PAL Mini inverted to solve this problem

Build-your-solutions1

Is your robot getting clotheslined?

Use PAL Mini upright to eliminate this problem

Need to see both the floor and hanging obstacles?

PAL USB provides the vertical FoV needed

Maximize cleaning efficiency

Maximize cleaning efficiency

Select the appropriate cleaning mode based on detected floor surface

Select the appropriate cleaning mode based on detected floor surface

Operate in diverse environments without adding more sensors/software

Operate in diverse environments without adding more sensors/software

Detect obstacles that 2D LiDAR can’t detect

Detect obstacles that 2D LiDAR can’t detect

Ensure efficient navigation around dynamic and cluttered environments

Ensure efficient navigation around dynamic and cluttered environments

Work in varying ambient lighting conditions

Work in varying ambient lighting conditions

Add visual intelligence for improved performance

Add visual intelligence for improved performance

Maximize cleaning efficiency

Maximize cleaning efficiency

Reduce BOM costs with a custom solution

Reduce BOM costs with a custom solution