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Quadruped robots, an important class of unmanned aerial vehicles, have broad potential for applications in education, service, industry, military, and other fields. Their independent positioning plays a key role for completing assigned tasks in a complex environment. However, positioning based on global navigation satellite systems (GNSS) may result in GNSS jamming and quadruped robots not operating properly in environments sheltered by buildings. In this paper, a tightly coupled LiDAR vision inertial odometer (LVIO) is proposed to address the positioning inaccuracy of quadruped robots, which have poor mileage information obtained though legs and feet structures only. With this optimization method, the point cloud data obtained by 3D LiDAR, the image feature information obtained by binocular vision, and the IMU inertial data are combined to improve the precise indoor and outdoor positioning of a quadruped robot. This method reduces the errors caused by the uniform motion model in laser odometer as well as the image blur caused by rapid movements of the robot, which can lead to error-matching in a dynamic scene; at the same time, it alleviates the impact of drift on inertial measurements. Finally, the quadruped robot in the laboratory is used to build a physical platform for verification. The experimental results show that the designed LVIO effectively realizes the positioning of four groups of robots with high precision and strong robustness, both indoors or outdoors, which verify the feasibility and effectiveness of the proposed method.

The analytical model of a permanent magnet eddy current coupler (PMECC) is mainly used for evaluation of its characteristics and the initial optimization of design. Based on the equivalent magnetic circuit method, this paper carries out analytical modeling for four typical PMECCs composed of surface-mounted and interior permanent magnet, slotted and non-slotted conductor rotors, which provides a theoretical basis for the subsequent research in this paper. The basic electromagnetic characteristics of the PMECCs are investigated by the established analytical model. Simultaneously, the analytical results about permeance, flux density, torque and power are verified by FEA simulation. The analysis results show that the slotted CR will obtain a much higher power density, and the iron loss mainly exists in the CRs. In addition, the analytical and FEA results agree well, which proves the reliability of the proposed, nearly unified analytical model.

In the process of extrapolating a lifetime distribution function under normal storage conditions through nonlinear accelerated degradation data, time indexes under the normal storage conditions are usually set to the mean value of time indexes under various accelerated stresses. However, minor differences in time indexes may lead to great changes in the assessment results. For such a problem, an accelerated degradation model of a nonlinear Wiener process based on a fixed time index is established first and meanwhile, the impact of the measurement error is considered. Then, the probability density function is normalized, and multiple unknown parameters are estimated by using fminsearch function in MATLAB and multiple iterations. Finally, the model is validated by accelerated degradation test data of accelerometers and the O-type rubber sealing rings. The results show that there is a difference of 30,710 h for accelerometers between the mean time to failure under normal storage conditions obtained by the proposed method and the mean time to failure when the time indexes are the mean value of those under various accelerated stresses, and the main cause of the difference is compared and analyzed. A similar phenomenon is observed in the case study of O-type rubber sealing rings.