Low-cost Retina-like Robotic Lidars Based on Incommensurable Scanning
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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.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jun 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 1; 2025: 1; 2026: 1.
8 papers.
- 2021R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping packagecited by 49
- 2023LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detectioncited by 12
- 2026UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perceptioncited by 4
- 2021Lidar with Velocity: Correcting Moving Objects Point Cloud Distortion from Oscillating Scanning Lidars by Fusion with Cameracited by 3
- 2022ECTLO: Effective Continuous-time Odometry Using Range Image for LiDAR with Small FoVcited by 2
- 2024PSS-BA: LiDAR Bundle Adjustment with Progressive Spatial Smoothingcited by 2
- 2023An Efficient Plane Extraction Approach for Bundle Adjustment on LiDAR Point cloudscited by 0
- 2025Which LiDAR scanning pattern is better for roadside perception: Repetitive or Non-repetitive?cited by 0
- 2026UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception15 Apr 2026
- 2025Which LiDAR scanning pattern is better for roadside perception: Repetitive or Non-repetitive?28 Oct 2025
- 2024PSS-BA: LiDAR Bundle Adjustment with Progressive Spatial Smoothing10 Mar 2024
- 2023An Efficient Plane Extraction Approach for Bundle Adjustment on LiDAR Point clouds29 Apr 2023
- 2023LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection29 Jan 2023
- 2022ECTLO: Effective Continuous-time Odometry Using Range Image for LiDAR with Small FoV17 Jun 2022
- 2021Lidar with Velocity: Correcting Moving Objects Point Cloud Distortion from Oscillating Scanning Lidars by Fusion with Camera18 Nov 2021
- 2021R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package10 Sep 2021