Hikrobot has recently introduced 3D Laser Profile Sensor in India for various application scenarios. It is expected to give a big boost to the manufacturing ecosystem of consumer electronics, lithium battery and PCB industries. Hikrobot’s 3D Laser Profile Sensor is a cutting-edge technology designed for high-precision, non-contact measurement applications. Based on laser triangulation measurement, 3D laser profile sensor can output high-frame point clouds, depth image and intensity image at micrometer level in real time. It is widely applicable to non-contact high-precision online 3D measurement scenes in consumer electronics, lithium battery, and PCB industries.
Real-time output of high-precision point cloud data The laser profile sensor uses 405 nm ultra-uniform fine blue light to accurately extract the contour line of the measured object. The customized large-iris lens ensures extremely high MTF resolution. At the same time, it perfectly cooperates with high dynamic range sensor and special Scheimpflug optical design to achieve clear imaging over the entire range in extremely complex scenarios.
The camera adopts a built-in integrated computing design, and its high-speed processing unit enables the maximum processing speed to reach 19 KHz/s.
Based on the principle of triangulation, the high-speed image acquisition module collects the laser line on the surface of the measured object with diffuse reflection. Through the high-precision image processing algorithm built into the hardware, the three-dimensional contour data of the surface of the measured object is calculated, and then the three-dimensional spatial information of the target object is restored through the relative movement between the camera and the measured object.
The high-speed image acquisition chip features large pixel size, high frame rate, and wide dynamic range. Through hardware acceleration bythe SOC chip, the camera can achieve a maximum frame rate of up to 49K Hz.
The center point extraction algorithm, combined with the subpixel super-resolution processing algorithm, improves the extraction accuracy to 0.05 pixels.
Multi-exposure fusion: Retain the valid grayscale information under different exposures, applicable to scenes with both high and low reflections.
Single-frame HDR: Achieve high-precision reconstruction of complex reflectivity scenes under high-speed scanning.
By extracting the halo features, different optical signals are filtered to suppress the influence of stray light halo on center point extraction.
Adopts built-in rich post-processing algorithms, including spatial filtering and time domain filtering, convenient for users to choose, without occupying the host CPU resources.
