Dual Lidar Research Articles

Dual LIDAR online calibration and mapping and perception system

Making autonomous mobile devices capable of autonomous positioning and map building in a GPS-denied environment as well as being able to circumvent people in the operating area simultaneously, is essential for many UGV appliances. In this paper, a mapping and positioning system using dual LIDAR is proposed for positioning and building maps. The system may also detect people in the operating space of the equipment using infrared heat maps. The localization and mapping information from each LIDAR is unified in a loosely coupled approach after simultaneous extrinsic calibration. We propose a method for constructing factor graph using LIDAR point cloud geometric features to optimally solve the dual LIDAR extrinsic in real time. We tested the localization accuracy with a publicly available dataset and three real-world scenarios and compared it with three existing methods. The test results in open-source datasets and real scenarios show that our proposed method improves the position and attitude estimation by up to 50% compared to the three existing methods, and the proposed dual LIDAR extrinsic calibration method can achieve an estimation accuracy of 0.05 m for the translational extrinsic and 1deg for the rotational extrinsic. In addition, our proposed method achieves well position and attitude estimation when other existing methods show severe drift in trajectory estimation in real scenarios. Thus, our proposed method is suitable for obtaining high accuracy measurements of LIDAR extrinsic parameters and for dense mapping and accurate localization in the environment of GNSS-denied and human mobility.

High-Precision SLAM Based on the Tight Coupling of Dual Lidar Inertial Odometry for Multi-Scene Applications

Simultaneous Localization and Mapping (SLAM) is an essential feature in many applications of mobile vehicles. To solve the problem of poor positioning accuracy, single use of mapping scene, and unclear structural characteristics in indoor and outdoor SLAM, a new framework of tight coupling of dual lidar inertial odometry is proposed in this paper. Firstly, through external calibration and an adaptive timestamp synchronization algorithm, the horizontal and vertical lidar data are fused, which compensates for the narrow vertical field of view (FOV) of the lidar and makes the characteristics of vertical direction more complete in the mapping process. Secondly, the dual lidar data is tightly coupled with an Inertial Measurement Unit (IMU) to eliminate the motion distortion of the dual lidar odometry. Then, the value of the lidar odometry after correcting distortion and the pre-integrated value of IMU are used as constraints to establish a non-linear least-squares objective function. Joint optimization is then performed to obtain the best value of the IMU state values, which will be used to predict the state of IMU at the next time step. Finally, experimental results are presented to verify the effectiveness of the proposed method.

Dual LiDAR experiment with buoy measurements as a target off the Kashima port

Dual LiDAR experiment with buoy measurements as a target off the Kashima port

Evaluation of dispersion model parameters by dual Doppler lidars over West London, England

Urban dispersion models have parameters for the turbulence and mixing height. We identify the parameters in meteorological pre-processors, which are, in principle, measurable by pulsed Doppler lidar. This technique measures radial velocity from the Doppler shifted wavelengths of backscattered laser pulses. First results obtained from single and dual lidar operations are described. Using two scanning lidars increases the range of parameters that can be sensed remotely. Scanned Dual Doppler lidar provides a novel remote sensing method for studying the rural-urban interface. Results are presented from a recent field experiment at an airfield site in West London. Results are compared with data from the Met Office operational dispersion model, NAME, a model using numerical weather forecast data. We show three methods for the urban mixing height. The paper concludes by considering the potential merits of dual-lidar remote sensing of urban dispersion model parameters.

Field test of a lidar wind profiler

Wind speeds and wind directions are measured remotely using an incoherent backscatter lidar system operating at a wavelength of 1.06 mm with a maximum repetition rate of 13 Hz. The principle of the measurements is based on following detectable atmospheric structures, which are transported by the wind (Taylor’s hypothesis). The characteristic size and lifetime of these structures are also inverted from the data. Initially, the lidar was pointed in the horizontal plane parallel to the wind direction to measure the horizontal wind speed from the displacement of the atmospheric structures along the lidar axis. Subsequently, the sensor was expanded with a time synchronous lidar that operated at an azimuth angle of about 15 deg with respect to the direction of the first lidar. The horizontal wind vector could then be measured over ranges of about 1.5 km using the geometry of the dual lidar and the transit times of the atmospheric structures between the two lidar axes. Results obtained with this dual lidar are comparable with the in situ measured wind vector. Finally, vertical profiles of the wind vector are measured to altitudes of about 1 km. This is realized by operating one lidar in the triangulation mode using a fast adjustable platform. The results obtained in this mode are in good agreement with in situ measured data from sensors on a 213-m-high meteorologically instrumented mast and with data provided by an acoustic sounder