Low-cost Retina-like Robotic Lidars Based on Incommensurable Scanning
This addresses the problem of limited mass adoption of high-performance lidars in autonomous robots like self-driving cars, though it appears incremental as it builds on existing scanning methods with new features.
The paper tackles the manufacturing difficulty and high cost of traditional mechanical scanning lidars for autonomous robots by proposing a robotic lidar sensor based on incommensurable scanning, which enables straightforward mass production and features a peaked central angular density similar to the human retina for eye-like attention.
High performance lidars are essential in autonomous robots such as self-driving cars, automated ground vehicles and intelligent machines. Traditional mechanical scanning lidars offer superior performance in autonomous vehicles, but the potential mass application is limited by the inherent manufacturing difficulty. We propose a robotic lidar sensor based on incommensurable scanning that allows straightforward mass production and adoption in autonomous robots. Some unique features are additionally permitted by this incommensurable scanning. Similar to the fovea in human retina, this lidar features a peaked central angular density, enabling in applications that prefers eye-like attention. The incommensurable scanning method of this lidar could also provide a much higher resolution than conventional lidars which is beneficial in robotic applications such as sensor calibration. Examples making use of these advantageous features are demonstrated.