As a non-contact inspection approach, vision technology usually undertakes the task of positioning, measuring and defect identification in the field of industrial automation. However, traditional visual programs at a high price are often designed for only a single category of products. Furthermore, the quantitative measurement tasks in the industry usually require a rigorous visual environment as well as hardware equipment, which implies a lack of generalization. Hence, it is imperative to establish a robust approach to break the barriers of multi-type product inspection, while reducing both system complexity and costs. This paper proposed an adaptive approach that performs inspections of the pins’ position for multi-type connectors. A joint strategy of deep neural network and pattern matching based on prior knowledge registration is constructed to achieve rapid positioning of sub-elements arranged in the target. Then, a hierarchical extraction method is designed to analyze features with various appearances and improve the anti-interference of vision-based system. The 3D version of the registration algorithm is embedded into the framework to determine abnormal positions of spatial data without reference. The proposed algorithm demonstrates a successful inspection of a total of 33 types of connectors, significant measurement robustness and adaptivity to the target pose, imaging status and feature diversity.

The step surmounting performance of a mobile robot is an important performance measure for obstaclenavigation. In this paper, a W-shaped track robot is taken as a research object and the step-climbing performance is analyzed theoretically. It is simulated by the RecurDyn software and is tested on a terrain simulation platform using a NDI dynamic measuring machine. In the independent step climbing process, the robot's front track sections of W-shaped track climb up the nosing of the step firstly and then the rear ones climb. Once the robot's position of center of gravity climbs over the nosing, the robot will climb up easily. According to different riser heights and positions of center of gravity, there are two situations for the climb of the rear tracks: (1) if the gravity center has been over the nosing when the rear tracks touch the nosing, then the robot's rear tracks will climb the steps softly without any impact; (2) and if not, then the robot's front tracks will rise and, then fall causing an impact. It is very easy for the robot to climb the step with a slope because of the guiding role of the slope. The robot can easily climb up the steps which are less than 240mm high, and the maximum tested step height is 320mm, but there should be a lower step in front of the step, and the robot's gravity center should be adjusted to a very low and forward position. In short, the W-shaped track mobile robot has a good performance for the overcoming of structured terrains.

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