# Low-cost Retina-like Robotic Lidars Based on Incommensurable Scanning

arXiv: https://arxiv.org/abs/2006.11034 · HTML: https://mlsanity.com/paper/2006.11034/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2020.

## Built on by (most cited first, 8 of 8)

- [R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package](https://mlsanity.com/paper/2109.07982/) (2021)
- [LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection](https://mlsanity.com/paper/2301.12515/) (2023)
- [UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception](https://mlsanity.com/paper/2604.14089/) (2026)
- [Lidar with Velocity: Correcting Moving Objects Point Cloud Distortion from Oscillating Scanning Lidars by Fusion with Camera](https://mlsanity.com/paper/2111.09497/) (2021)
- [ECTLO: Effective Continuous-time Odometry Using Range Image for LiDAR with Small FoV](https://mlsanity.com/paper/2206.08517/) (2022)
- [PSS-BA: LiDAR Bundle Adjustment with Progressive Spatial Smoothing](https://mlsanity.com/paper/2403.06124/) (2024)
- [An Efficient Plane Extraction Approach for Bundle Adjustment on LiDAR Point clouds](https://mlsanity.com/paper/2305.00287/) (2023)
- [Which LiDAR scanning pattern is better for roadside perception: Repetitive or Non-repetitive?](https://mlsanity.com/paper/2511.00060/) (2025)

## Abstract (arXiv)

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.