This project is used for advanced driver assistance systems (ADAS)automatic driving. At present, our project will use a more sensitive CMOS single photon detector array to reduce the number of photons required for detection to less than ten, in order to break through the cost barriers of applications of LiDARestablish low-cost, high-performance LiDAR modules.

Through patented wearable sensor fusion technology, human 3D motions can be captured in real-time which allow 7-DOF robotic armdexterous robotic hand to perform anthropomorphic motiongrasping action. Integrated with eye-in-hand visual module, the adaptive gripper can intelligently decide optimal grasping strategy to ensure success grasping of arbitrary shape of objects in smart manufacturing applications.

Based on deep learning camera/radar object detectiontracking technology, the proposed road side unit (RSU) system has achieved over 95 vehicle detection accuracy within 100m detection range in the processing performance of 10fps under nVidia Jetson Xavier platform. Compared to the 32-beam lidar based RSU, the proposed RSU achieves 97 reduction of sensor cost that exhibits high competitiveness in deployment cost. The proposed RSU system has been verified in fieldswe are now cooperating with an industry partner to deploy the RSU system in both TainanTao-Yuan cities.