Glass bottles must be thoroughly inspected before they are used for packaging. However, the vision inspection of bottle bottoms for defects remains a challenging task in quality control due to inaccurate localization, the difficulty in detecting defects in the texture region, and the intrinsically nonuniform brightness across the central panel. To overcome these problems, we propose a surface defect detection framework, which is composed of three main parts. First, a new localization method named entropy rate superpixel circle detection (ERSCD), which combines least-squares circle detection and entropy rate superpixel (ERS) with an improved randomized circle detection, is proposed to accurately obtain the region of interest (ROI) of the bottle bottom. Then, according to the structure-property, the ROI is divided into two measurement regions: central panel region and annular texture region. For the former, a defect detection method named frequency-tuned anisotropic diffusion super-pixel segmentation (FTADSP) that integrates frequency-tuned salient region detection (FT), anisotropic diffusion, and an improved superpixel segmentation is proposed to precisely detect the regions and boundaries of defects. For the latter, a defect detection strategy called wavelet transform multiscale filtering (WTMF) based on a wavelet transform and a multiscale filtering algorithm is proposed to reduce the influence of texture and to improve the robustness to localization error. The proposed framework is tested on four data sets obtained by our designed vision system. The experimental results demonstrate that our framework achieves the best performance compared with many traditional methods.

This paper addresses the problem of autonomous servoing control an unmanned aerial manipulator with the capability of grasping target objects by using computer vision. Specifically, a practical visual servo control using spherical projection model is proposed. The aerial manipulator is an unmanned aerial vehicle (UAV) equipped with a robotic arm that greatly increases the freedom and operational flexibility of the end gripper. However, such a system produces complexity in its kinematics, dynamics and control duo to the coupling characteristics of the two parts. A novel passivity-like visual error equation of the image features is established by using the spherical camera geometry dynamics with an eye-in-hand configuration. To further improve the grasping performance, a task-priority control scheme is utilized with one main task and several sub-tasks, i.e., controlling the gripper position and orientation, vertically aligning the CoG (center of gravity) and avoiding the joint limitation. Simulation results are provided to illustrate and assess the performance of the proposed visual servo control. Experimental results performed in outdoor environments support well the practical analysis and effectiveness of autonomous aerial manipulation.

In this article, an adaptive force tracking impedance control strategy is investigated for an aerial manipulator in physical interaction with uncertain contact environments. Based on the modified target impedance model, an adaptive impedance control method is proposed to accomplish aerial interaction in uncertain environments while maintaining a stable contact force, wherein the environment parameters of location and stiffness are estimated online to generate a reference position trajectory. Then, in order to ensure the tracking performance of the aerial manipulator, a robust pose tracking controller is designed, including a barrier function-based position controller and an adaptive attitude controller. Both proposed position and attitude controllers can ensure finite-time convergence of the state variable without the priori boundary information of disturbances. In particular, the position state variable can converge to a predefined neighborhood of zero from any initial state, and the control gain is not overestimated. The stability of the proposed strategy is analyzed via Lyapunov tools. Simulations and real-world experiments are conducted to illustrate the feasibility and performance of the proposed control strategy. Note to Practitioners —The motivation of this article is to investigate an adaptive force tracking impedance control strategy for aerial physical interaction with uncertain contact environments. In the existing impedance control schemes for aerial manipulators, the environment parameter of location or stiffness is often required to be utilized in controller design. However, in practical cases, the environmental parameters are not known precisely. Thus, this article presents an adaptive impedance method to automatically generate the reference position trajectory and achieve a stable contact force. Additionally, the tracking performance of the aerial manipulator is inevitably subject to uncertainties and disturbances. To ensure tracking convergence, traditional robust controllers generally involve high control gains than the known upper bounds of the disturbances. The main disadvantage of those controllers is that the control gain is often overestimated when the disturbance decreases. To address this issue, a barrier function-based position controller is proposed for the aerial manipulator, where the priori boundary information of disturbances is not needed and the control gain is adaptively adjusted according to the amplitude of disturbances. The stability and convergence of the proposed strategy are analyzed mathematically, and the experiments using an aerial manipulator provide promising results.

This article investigates a robust variable impedance control methodology for aerial manipulators to realize compliant and safe interaction tasks. Considering that the stability characteristics are generally overlooked in existing variable impedance controllers of the aerial manipulator, state-independent stability conditions are applied for time-varying impedance profiles to ensure the exponential stability of the desired variable impedance dynamics (DVID) as well as the boundedness of the state variables in the DVID. A command trajectory variable is introduced for converting the impedance control issue to a particular tracking issue, and then, a robust variable impedance controller based on the wrench estimator is designed to guarantee the exponential convergence of the translational states and impedance error of the aerial manipulator. The designed impedance controller is structurally simple and results in low implementation costs. Next, an improved attitude control approach with the command filter is developed for global flight attitude stability without any singularities or ambiguities, where the filter is introduced to avoid computing the derivative signals of the generalized force input. Finally, the effectiveness of the proposed control method is illustrated via numerical simulations and interaction experiments with different targets in real scenarios.