DS80 uses high-speed, low-latency, and high-precision self-developed SLAM technology.
The high-performance SOC has greatly improved computing power and supports multiple advanced working modes such as high-speed and high-precision independent VIO, SLAM/CSLAM, end-cloud collaboration, real-time loop detection, high-speed QR code/spatial anchor assisted positioning, etc.
Deep collaboration among multiple sensors enables faster, more accurate and more stable positioning.
| I HAVE | Cycles | Ave RTE (%) | Max RTE (%) | Ave ARE (°) | Max ARE (°) |
|---|---|---|---|---|---|
| SN: 21004424 | 1 | 0.12 | 0.33 | 0.51 | 1.58 |
| 2 | 0.11 | 0.48 | 0.47 | 2.25 | |
| 3 | 0.12 | 0.50 | 0.53 | 2.18 | |
| Average | 0.11 | 0.44 | 0.51 | 2.00 | |
| Remark | Test conditions: 10x5m office test environment, 20-30m moving trajectory RTE: Relative Translation Error relative translation error ARE: Absolute Rotation Error |
||||

Passive binocular vision:
With a large field of view (110°), high resolution (640*480@60fps), and an effective distance of 5.5 meters (error <3%), it performs excellently in bright light environments and is suitable for modeling and obstacle avoidance in open scenes.
Active iTOF (Sony VGA):
940nm anti-interference wavelength, ultra-high accuracy (error <1%) within 0.2-4 meters, 30fps frame rate, and output of depth maps, point clouds, and IR images. Its accuracy in low-light and indoor environments far exceeds that of binoculars. It supports switching between single-frequency (1.5m) and dual-frequency (4m) modes.
The dual engines can work simultaneously and seamlessly integrate with VSLAM to provide real-time environmental depth information, laying a solid foundation for navigation, obstacle avoidance, and 3D reconstruction.
The independent hardware CNN engine is a key breakthrough! It breaks away from the dependence on the computing power of the main control system and realizes localized real-time AI reasoning. It supports the access of multiple video sources such as fisheye, TOF, RGB, and can deploy multiple AI models in parallel. Combining VSLAM and depth information, it realizes advanced intelligent functions such as 3D gesture recognition and tracking, human skeleton extraction, 3D face anti-counterfeiting recognition, object recognition and spatial semantic segmentation, and scene understanding. Perfectly compatible with OpenCV & Open VINO, which allows for easy deployment of models from open source communities (such as Open Model Zoo) or user-trained models, with plug-and-play functionality, significantly shortening the R&D cycle.
Hardware-based H.265 video compression significantly saves valuable transmission bandwidth and reduces the overall system load.
Localized processing capabilities significantly lower the development and integration threshold.
Supports Windows/Linux/Android, and provides wrappers for ROS/ROS2, Unity, C/C++, Python, Java JNI, etc. API, seamlessly connect to various development frameworks.
The USB Type-C is used to connect to the main controller, and sensors such as lidar can be connected through the expansion interface. It supports multi-machine cascading to meet complex system requirements.
Passed CE, FCC, RoHS, CB, FDA Class I laser safety certifications, and is accepted in the global market.









SeerSense® DS80

SDK

Tool Chain
| Features | Specification | Remark |
|---|---|---|
| processor | High performance SOC | |
| camera | ||
| -Binocular fisheye camera | 1280x800/640x400, 60fps DFOV150°/HFOV130°/VFOV74° |
Monochrome, global exposure 80mm baseline |
| -Color camera | 8MP(4192x3104), 30fps DFOV79.9°/HFOV68°/VFOV53° |
Camera: 8.2MP/13MP (MAX) video: VGA/720P/1080P @ 30fps |
| -Depth camera | 640x480/320x240, 30fps DFOV78°/HFOV64°/VFOV50° |
depth error=<1% 940nm |
| IMU | 9 Axis | 1000 Hz for SLAM fusion |
| CNN Engine | Dual engine | Parallel processing |
| Binocular Depth Engine | VGA/720P SGBM(Semi-Global Block Match) |
50/60fps, 6.5 meter |
| SLAM Engine | 500-1000Hz millimeter-level accuracy | Local processing, multiple working modes |
| Power consumption | Avg 2.8W | Full load |
| powered by | 5V 3A | |
| interface | USB Type C | Camera data stream, depth, AI image, 6DoF output |
| Debug Port | UART, Sync Pin | |
| Weight and size | 93g | 119Lx23Dx24H | LxDxH(mm) |
| SDK | VIO, CSLAM, 3D reconstruction, depth/point cloud (SGBM/TOF), object recognition, gesture, plane detection, RGBD | |
| Toolchain | Open VINO, Open CV, Xvxdk-viewer Demo Tool | |
Copyright © Shanghai Xvisio Sensing Technology Co., Ltd. All Rights Reserved