Aiming at the influence of the energy distribution of incident light on the traditional location algorithm of four-quadrant detector (4-QD), the generation rule of measurement error is analyzed. A model to express the energy distribution of the light spot of 4-QD is established by using characteristic parameters, and the measurement error model related to the characteristic parameters is derived. In the actual system, for different spot locations, we can use this model to fit the energy distribution, and get the spot characteristic parameters of the system, and then use it to calculate the measurement error caused by the traditional algorithm in 4-QD system. In the experiment, the energy distribution image of the incident beam is obtained by the beam quality analyzer, and the actual moving distance of the spot is compared with the calculation result of the traditional measurement algorithm. From the experimental results, it can be proved that the measurement error model of the four-quadrant detector, which is described in this paper, is consistent with the experimental results. It can further modify the calculation results of the 4-QD system in practical applications, to improve the measurement accuracy.
The traditional pulse laser ranging system based on the measurement of time of flight often ignores the nonlinear influence of the intensity of the echo light power on the range error of the receiver system. Based on the transistor model (Gummel-Poon model), this paper makes a systematic modeling of the pulsed laser range finding receiver system. By means of computer aided analysis, the relationship between the input current waveform and the leading edge of the response pulse of the receiving system is analyzed. And thus, the relationship model of the echo light power and front of response echo pulse is derived in the paper. Based on the above model and by involving the method of differential threshold time discrimination, the walking error in the laser ranging system is corrected. Finally, the experimental results show that this method can effectively correct the nonlinear error caused by the fluctuation of the echo power and improve the accuracy of the ranging system.
Laser and visual imagery have been broadly utilized in computer vision and mobile robotics applications because these sensors provide complementary information. So we focus attention on the fusion of 1-D laser rangefinder and camera. However, finding the transformation between the camera and the 1-D laser rangefinder is the first necessary step for the fusion of information. Many algorithms have been proposed to calibrate camera and 2-D or 3-D laser rangefinder, but few methods for 1-D laser rangefinder. In this paper, we propose a robust extrinsic calibration algorithm that is implemented easily and has small calibration error. Due to the 1-D laser rangefinder only returns a data in one dimension direction, it is difficult to build geometric constraint equations like 2-D laser rangefinder. So we are no longer constrained to build constraint equations to finish calibration. Due to the spot of the single-point laser rangefinder we commonly use is mostly invisible, we can determine the full calibration even without observing the laser rangefinder observation point in the camera image. We evaluate the proposed method demonstrating the efficiency and good behavior under noise. Finally we calibrate the installation error of camera utilizing the calibration result.