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Smart Auto- Core Technology
- Based on the foundation of proprietary technologies and SenseCore AI infrastructure,
SenseTime has rapidly opened up AI application in multiple vertical scenarioses, and is empowering various industries.
- 01Camera Perception
- 02LiDAR Perception
- 03Multi-Sensor Fusion
- 04Behavior Prediction of Vehicle / Pedestrian / Bicycle
- 05Path Planning, Decision Making and Control
- 06HD Map and Localization
- 07Adaptation and Deployment of Multi-chip Platform
- 08Camera Configuration
- 09Quality Management System
01 / 09
Camera Perception
With SenseTime’s experience in computer vision, the camera perception technology can detect lane lines, roadsides, drivable areas, vehicles, pedestrians, traffic signs, and traffic lights accurately through a monocular camera. Meanwhile, the high-performance lightweight target detection, tracking and recognition, were widely adopted in the Driver Monitoring System, Occupancy Monitoring System, and Facial Recognition Access System. The product can operate under complex lighting conditions such as dark light and backlight.
02 / 09
LiDAR Perception
Our LiDAR perception algorithm supports different types of LiDAR and application scenarioses. It provides accurate detection and tracking of traffic participants and unknown objects under various scenarioses such as autonomous driving and V2X.
03 / 09
Multi-Sensor Fusion
Our multi-sensor fusion system supports different combinations of different sensors to yield better results in lower latency, higher precision and fault tolerance.
04 / 09
Behavior Prediction of Vehicle / Pedestrian / Bicycle
It can accurately predict behaviors of vehicles, pedestrians or bicycles in complex traffic scenes, which include the intention of turning, lane changing and road crossing, and the awareness of surrounding environments, as well as multiple potential trajectories. It provides reliable information for smarter planning and decision-making for autonomous driving.
05 / 09
Path Planning, Decision Making and Control
By integrating multiple modules, vehicle movements and surrounding environment, the technology enables a safe, smart and smooth decision-making and path planning process under complex driving scenarioses, while providing accurate control of the vehicle.
06 / 09
HD Map and Localization
We can create high definition 3D maps at city scale with multi-sensor fusion technologies, which include point cloud map, localization map, semantic map, routing map. In addition, based on the HD maps, we provide high-precision localization in real time.
07 / 09
Adaptation and Deployment of Multi-chip Platform
Based on SenseParrots, our proprietary AI deep learning platform, the self-developed FPGA deployment toolchain and hardware accelerator being employed, our algorithm can be applied to a variety of mainstream SoCs with great flexibility and ease. This will promote the mass production of autonomous driving technology. Leveraging on self-developed HPC and edge computing deployment framework, the product utilizes the computing resource of automotive AI chips (NPU/DSP/GPU) targeting the mainstream ECUs in the automotive cabin industry to achieve low latency and less CPU/memory usage.
08 / 09
Camera Configuration
The product adapts to mainstream in-cabin cameras（IR/RGB/RGB-IR） in the market to form optimized quantitative indicators for image quality to ensure high product consistency on the system level.
09 / 09
Quality Management System
SenseTime established a comprehensive quality management system, and was granted the ISO26262 ASIL-B functional safety certification and ASPICE L2 certification in February 2020 and July 2020, respectively.
01 / 09
Camera Perception
With SenseTime’s experience in computer vision, the camera perception technology can detect lane lines, roadsides, drivable areas, vehicles, pedestrians, traffic signs, and traffic lights accurately through a monocular camera. Meanwhile, the high-performance lightweight target detection, tracking and recognition, were widely adopted in the Driver Monitoring System, Occupancy Monitoring System, and Facial Recognition Access System. The product can operate under complex lighting conditions such as dark light and backlight.
02 / 09
LiDAR Perception
Our LiDAR perception algorithm supports different types of LiDAR and application scenarioses. It provides accurate detection and tracking of traffic participants and unknown objects under various scenarioses such as autonomous driving and V2X.
03 / 09
Multi-Sensor Fusion
Our multi-sensor fusion system supports different combinations of different sensors to yield better results in lower latency, higher precision and fault tolerance.
04 / 09
Behavior Prediction of Vehicle / Pedestrian / Bicycle
It can accurately predict behaviors of vehicles, pedestrians or bicycles in complex traffic scenes, which include the intention of turning, lane changing and road crossing, and the awareness of surrounding environments, as well as multiple potential trajectories. It provides reliable information for smarter planning and decision-making for autonomous driving.
05 / 09
Path Planning, Decision Making and Control
By integrating multiple modules, vehicle movements and surrounding environment, the technology enables a safe, smart and smooth decision-making and path planning process under complex driving scenarioses, while providing accurate control of the vehicle.
06 / 09
HD Map and Localization
We can create high definition 3D maps at city scale with multi-sensor fusion technologies, which include point cloud map, localization map, semantic map, routing map. In addition, based on the HD maps, we provide high-precision localization in real time.
07 / 09
Adaptation and Deployment of Multi-chip Platform
Based on SenseParrots, our proprietary AI deep learning platform, the self-developed FPGA deployment toolchain and hardware accelerator being employed, our algorithm can be applied to a variety of mainstream SoCs with great flexibility and ease. This will promote the mass production of autonomous driving technology. Leveraging on self-developed HPC and edge computing deployment framework, the product utilizes the computing resource of automotive AI chips (NPU/DSP/GPU) targeting the mainstream ECUs in the automotive cabin industry to achieve low latency and less CPU/memory usage.
08 / 09
Camera Configuration
The product adapts to mainstream in-cabin cameras（IR/RGB/RGB-IR） in the market to form optimized quantitative indicators for image quality to ensure high product consistency on the system level.
09 / 09
Quality Management System
SenseTime established a comprehensive quality management system, and was granted the ISO26262 ASIL-B functional safety certification and ASPICE L2 certification in February 2020 and July 2020, respectively.
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