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Laser-based light detection and ranging (lidar) plays a significant role in both scientific and industrial areas. However, it is difficult for existing lidars to achieve high speed, high precision, and long distance simultaneously. Here, we demonstrate a high-performance lidar based on a chip-scaled soliton microcomb (SMC) that can realize all three specialties simultaneously. Aided by the excellent properties of ultrahigh repetition rate and the smooth envelope of the SMC, traditional optical frequency comb (OFC)-based dispersive interferometry is heavily improved and the measuring dead zone induced by the mismatch between the repetition rate of the OFC and resolution of the optical spectrum analyzer is totally eliminated. Combined with an auxiliary dual-frequency phase-modulated laser range finder, the none-dead-zone measurable range ambiguity is extended up to 1500 m. The proposed SMC lidar is experimentally implemented in both indoor and outdoor environment. In the outdoor baseline field, real-time, high-speed (up to 35 kHz) measurement of a long distance of ∼ 1179    m is achieved with a minimum Allan deviation of 5.6 μm at an average time of 0.2 ms (27 nm at an average time of 1.8 s after high-pass filtering). The present SMC lidar approaches a compact, fast, high-precision, and none-dead zone long-distance ranging system, aimed at emerging applications of frontier basic scientific research and advances in industrial manufacturing.

An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%∼78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 × 0.8 × 1 ∼ 2 × 0.8 × 1 m in the field of view (FOV) is indicated by the experimental results.

We perform a long distance measurement up to 1.2 km on the outdoor baseline by electro-optic dual-comb interferometry. A frequency comb pair is developed by phase modulating a continuous laser with a narrow linewidth, and the slightly different repetition frequencies are synchronized to the Rb clock via the signal generators. A RF electrical comb can be generated by multi-wavelength heterodyne interferometry, and thus, a series of synthetic wavelengths can be obtained, whose phases can be used to determine the distances. Compared with the reference values, the experimental results show an agreement within 379 μm in the 1180 m range. In the long-time experiments, the Allan deviation can be below 20 μm with an averaging time of 10 s, and can be further improved to be less than 600 nm when the averaging time is above 350 s at 435 m and 1180 m, respectively.

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We propose an interferometric method that enables to measure a distance by the intensity measurement using the scanning of the interferometer reference arm and the recording of the interference fringes including the brightest fringe. With the consideration of the dispersion and absorption of the pulse laser in a dispersive and absorptive medium, we investigate the cross-correlation function between two femtosecond laser pulses in the time domain. We also introduce the measurement principle. We study the relationship between the position of the brightest fringe and the distance measured, which can contribute to the distance measurement. In the experiments, we measure distances using the method of the intensity detection while the reference arm of Michelson interferometer is scanned and the fringes including the brightest fringe is recorded. Firstly we measure a distance in a range of 10 µm. The experimental results show that the maximum deviation is 45 nm with the method of light intensity detection. Secondly, an interference system using three Michelson interferometers is developed, which combines the methods of light intensity detection and time-of-flight. This system can extend the non-ambiguity range of the method of light intensity detection. We can determine a distance uniquely with a larger non-ambiguity range. It is shown that this method and system can realize absolute distance measurement, and the measurement range is a few micrometers in the vicinity of Nl(pp), where N is an integer, and lpp is the pulse-to-pulse length.

Multiple instrument stations, based on spherical coordinate measurements, are often used in the measurement of large objects. A data fusion method is proposed to derive optimal estimations of the positions of the object features, measured by more than one device. First, each device has a dedicated coordinate system that is linked together through the measurement of common points. Second, the weighted mean coordinates are derived. The covariance matrix of the sensory, covering of the radial distance and the angles, is propagated to get a weight matrix. Third, a nonlinear function is minimized to determine the optimized coordinate of the points. Monte Carlo error propagation is utilized to estimate the uncertainty of the fusion points. Simulation of the fusion algorithms is performed using laser tracking and laser radar. The fusion algorithm experiments are performed using two laser tracking stations. Simulation and experiments prove that the fusion method improves the precision of the measurements of an object's location, due to incorporating the degree of uncertainty for each measurement point.