US: RoboSense, a leader in LiDAR perception technology, has announced the revolutionary RS-IPLS Intelligent Perception LiDAR system, the first hardware/software algorithm solution for the mass production of safer autonomous cars. A high-performance autonomous driving system, the RS-IPLSfeatures real-time data pre-processing and a “gaze” function similar to human eyes. The RoboSense system is inexpensive, 1/400th the price of traditional 64-line LiDAR systems, designed for the mass production of vehicles at a low price.
With RoboSense’s more than 10 years algorithm experience, the RS-IPLS, based on high-performance MEMS solid-state LiDAR, outputs highest resolution color point cloud data by merging 2D imagery hardware with unique RoboSense RS-LiDAR-Algorithm deep learning sensing algorithms. The algorithms achieve object level information for Region of Interest (ROI) detection area in real-time. In early 2017, RoboSense became the first LiDAR vendor to introduce laser-aerodynamic environment-aware RS-LiDAR-Algorithms, with LiDAR hardware for a large number of partners with P-series LiDAR solutions for different applications.
The RS-IPLS features the new RoboSense RS-LiDAR-Gaze “Gaze” Technology. When the system perceives a target in its field of view, it initiates a “gaze” process that instantly locks the target for ROI processing, achieving the clearest, most stable environmental data. The LiDAR low-level architecture maintains vigilance, constantly capturing areas of interest, allowing the “gaze” to transfer high-quality feedback.
The RS-IPLS also provides richer three-dimensional spatial data (X, Y, Z, R, G, B) in real-time from the bottom layer, reducing delay caused by external fusion. Data pre-processing is performed by the AI algorithm, with the ROI repeatedly detected for farther distance and more accurate perception results, with reduced stress to the central data processing unit.
The RS-IPLS is based on RoboSense’s solid-state LiDAR technology, RS-LiDAR-M1pre, which combines RoboSense RS-LCDF LiDAR, camera fusion, RS-LCDF, RS-LiDAR-Algorithms, and RS-LiDAR-Gaze.