Motion capture based on multi-camera is widely used in the quantification of animal locomotor behaviors and this is one of the main research methods to reveal the physical laws of animal locomotion and to inspire the design and realization of bionic robot. It has been found that the multi-camera layout patterns greatly affect the effect of motion capture. Due to the researches for animals of diverse species, determining the most appropriate layout patterns to achieve excellent capture performance remains an unresolved challenge. To improve the capturing accuracy, this investigation focuses on the method of multi-camera layout as a motion capture system for diverse animals with significant differences in outward appearance characteristics and locomotor behaviors. The demand boundaries of motion capture are determined according to the appearance types (shapes and space volume) and the behavior characteristics of the animals, resulting in the matching principle of the typical multi-camera layout patterns (arch, annular and half-annular) with diverse animals. The results of the calibration experiments show that the average standard deviation rate (ASDR) of multi-camera system in the half-annular layout patterns (0.52%) is apparently smaller than that of the other two patterns, while its intersecting volume is the largest among the three patterns. The ASDR at different depths of field in a half-annular layout demonstrate that the greater depth of field is conducive to improving the precision of the motion capture system. Laboratory experiments of the motion capture for small animals (geckos and spiders) employed the multi-camera system locked in the 3-D force measuring platform in a half-annular layout pattern indicate that the ASDR of them could reach less than 3.8% and their capturing deviation rate (ACDR) are respectively 3.43% and 1.74%. In this report, the correlations between the motion capture demand boundaries of small animals and the characteristics of the multi-camera layout patterns were determined to advance the motion capture experimental technology for all kinds of small animals, which can provide effective support for the understanding of animal locomotion.

The existing Bug algorithms, which are the same as wall-following algorithms, offer good performance in solving local minimum problems caused by potential fields. However, because of the odometer drift that occurs in actual environments, the performance of the paths planned by these algorithms is significantly worse in actual environments than in simulated environments. To address this issue, this article proposes a new Bug algorithm. The proposed algorithm contains a potential field function that is based on the relative velocity, which enables the potential field method to be extended to dynamic scenarios. Using the cumulative changes in the internal and external angles and the reset point of the robot during the wall-following process, the condition for state switching has been redesigned. This improvement not only solves the problem of position estimation deviation caused by odometer noise but also enhances the decision-making ability of the robot. The simulation results demonstrate that the proposed algorithm is simpler and more efficient than existing wall-following algorithms and can realise path planning in an unknown dynamic environment. The experimental results for the Kobuki robot further validate the effectiveness of the proposed algorithm.

The meniscus-confined electrodeposition (MCED) technique offers advantages such as low cost and wide applicability, making it a promising method in the field of micro/nanofabrication. However, unstable meniscal morphology and poor deposition quality during planar deposition in MCED necessitate the development of improved methods. Therefore, a planar adaptive micro-tuning deposition method (PAMTDM), which utilizes the positioning technology of scanning electrochemical cell microscopy (SECCM) and employs a singular value decomposition (SVD) planar fitting method to determine the flatness of the deposition plane, is proposed. An adaptive micro-tuning motion mode was proposed by analyzing the variation patterns of the meniscus. Moreover, a combination of multi-physics finite element simulations and orthogonal experimental methods was introduced to determine the optimal motion parameters. The experimental results demonstrate that the PAMTDM effectively addresses the issues encountered during planar growth. Compared to the point-by-point deposition method, the PAMTDM achieves a threefold increase in deposition speed for continuous deposition of 105-μm-long line segments in two-dimensional planes, with a deposition current error of less than 0.2 nA. In conclusion, the proposed method provides significant insights into the broad future applications of MCED.