Comparative Analysis of SLAM Algorithms for Mechanical LiDAR and Solid-State LiDAR

Zhou, Baoding; Xie, Doudou; Chen, Shoubin; Mo, Haoquan; Li, Chunyu

doi:10.1109/jsen.2023.3238077

Cited by 13 publications

(2 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mechanical LiDAR is expensive, bulky, and vulnerable. Low-cost solid-state LiDAR is gradually becoming a mainstream product to expand the LiDAR market [3]. Currently, the mainstream solid-state LiDAR has micro-electromechanical system (MEMS) LiDAR [4], flash LiDAR [5], and optical phased array (OPA) LiDAR [6].…”

Section: Introductionmentioning

confidence: 99%

Wide Range Controllable Direction Single Emission Peak Microstructured Lasers Array

Yang,

Wang,

Wang

et al. 2024

IEEE Photonics J.

View full text Add to dashboard Cite

In this paper, a single emission peak microstructured lasers array for beam control is proposed. And lasers in the array can emit beams in specific directions with low vertical divergence angles. The initial phase control is introduced to solve the problem of multiple emission peaks in a vertical far-field pattern. Both simulation and experimental analyses corroborate that the intensity of high-order diffraction peaks can be suppressed by introducing an appropriate starting position. Experimental results showcase the achievement of a low vertical divergence angle of 0.95° and an expansive angle sweep range of 61.2°. Furthermore, leveraging a taper structure, a horizontal divergence angle of 3.7° and a typical optical output power of 28 mW are obtained.

show abstract

Section: Introductionmentioning

confidence: 99%

Wide Range Controllable Direction Single Emission Peak Microstructured Lasers Array

Yang,

Wang,

Wang

et al. 2024

IEEE Photonics J.

View full text Add to dashboard Cite

show abstract

“…Simultaneous Localization and Mapping (SLAM) technology is an important technology in the field of mobile robotics, which focuses on the mapping and localization of robots in unknown scenarios, and completes the estimation of the robot's position and the construction of the map of the environment through the sensors carried by the robots themselves, so as to realize the autonomous work of the robots in unknown environments 1 .The working environments of mobile robots have been transformed from single experimental test scenarios to more and more complex real worlds, such as autonomous driving 2 , household robots 3 , and warehouse transportation 4 . These uncertainties bring great challenges to the autonomous localization and environment sensing of mobile robots, and loopback detection can correct the error drift, which plays a very important role in constructing high-precision global maps 5 .…”

Section: Introductionmentioning

confidence: 99%

3D LiDAR localization and mapping method incorporating inertial measurement unit

Luo,

Cheng,

2023

Optoelectronic Imaging and Multimedia Technology X

View full text Add to dashboard Cite

Simultaneous localization and mapping (SLAM) technology is widely used in smart factories, logistics, unmanned vehicles, high precision mapping and other fields, where inaccurate positioning or even failure is the key problem to be improved and solved by LiDAR SLAM algorithm. In this paper, we propose a loosely coupled SLAM algorithm based on lidar and inertial measurement unit (IMU). Firstly, linear interpolation of the laser point cloud is performed by introducing IMU data to correct the point cloud distortion. Second, a height threshold and a dynamic clustering threshold are introduced in the point cloud segmentation part to determine the classification. Again, the cumulative error is effectively avoided by using Scan-Context descriptors, and the next step is executed to find matching loopback frames based on the Euclidean distance, and the loopback constraints are added after the successful verification of both. Finally, a local map consisting of key frames is aligned with the current frame to obtain the inter-frame matching error, and then a joint optimization function is constructed jointly with the IMU pre-integration error and the loopback detection constraint to solve the laser odometer pose. The results on the KITTI dataset show that the improved laser odometer accuracy is higher than that of the LeGO-LOAM scheme in compliance with the odometer real-time requirements.

show abstract

A review of ToF-based LiDAR

Ma,

Zhuo,

Qiu

et al. 2024

J. Semicond.

View full text Add to dashboard Cite

In recent years, propelled by the rapid iterative advancements in digital imaging technology and the semiconductor industry, encompassing microelectronic design, manufacturing, packaging, and testing, time-of-flight (ToF)-based imaging systems for acquiring depth information have garnered considerable attention from both academia and industry. This technology has emerged as a focal point of research within the realm of 3D imaging. Owing to its relatively straightforward principles and exceptional performance, ToF technology finds extensive applications across various domains including human−computer interaction, autonomous driving, industrial inspection, medical and healthcare, augmented reality, smart homes, and 3D reconstruction, among others. Notably, the increasing maturity of ToF-based LiDAR systems is evident in current developments. This paper comprehensively reviews the fundamental principles of ToF technology and LiDAR systems, alongside recent research advancements. It elucidates the innovative aspects and technical challenges encountered in both transmitter (TX) and receiver (RX), providing detailed discussions on corresponding solutions. Furthermore, the paper explores prospective avenues for future research, offering valuable insights for subsequent investigations.

show abstract

Comparative Analysis of SLAM Algorithms for Mechanical LiDAR and Solid-State LiDAR

Cited by 13 publications

References 51 publications

Wide Range Controllable Direction Single Emission Peak Microstructured Lasers Array

Wide Range Controllable Direction Single Emission Peak Microstructured Lasers Array

3D LiDAR localization and mapping method incorporating inertial measurement unit

A review of ToF-based LiDAR

Contact Info

Product

Resources

About