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When the mobile manipulator is traveling on an unconstructed terrain, the external disturbance is generated. The load on the end of the mobile manipulator will be affected strictly by the disturbance. The purpose of this paper is to reject the disturbance and keep the end effector in a stable pose all the time, a control method is proposed for the onboard manipulator.

In this paper, the kinematics and dynamics models of the end pose stability control system for the tracked robot are built. Through the guidance of this model information, the control framework based on active disturbance rejection control (ADRC) is designed, which keeps the attitude of the end of the manipulator stable in the pitch, roll and yaw direction. Meanwhile, the control algorithm is operated with cloud computing because the research object, the rescue robot, aims to be lightweight and execute work with remote manipulation.

The challenging simulation experiments demonstrate that the methodology can achieve valid stability control performance in the challenging terrain road in terms of robustness and real-time.

This research facilitates the stable posture control of the end-effector of the mobile manipulator and maintains it in a suitable stable operating environment. The entire system can normally work even in dynamic disturbance scenarios and uncertain nonlinear modeling. Furthermore, an example is given to guide the parameter tuning of ADRC by using model information and estimate the unknown internal modeling uncertainty, which is difficult to be modeled or identified.

To present an open architecture for real‐time sensory feedback control of a dual‐arm industrial robotic cell. The setup is composed of two industrial robot manipulators equipped with force/torque sensors and pneumatic grippers, a vision system and a belt conveyor.

The original industrial robot controllers have been replaced by a single PC with software running under a real‐time variant of the Linux operative system.

The new control architecture allows advanced control schemes to be developed and tested for the single robots and for the dual‐arm robotic cell, including force control and visual servoing tasks.

An advanced user interface and a simulation environment have been developed, which permit fast, safe and reliable prototyping of planning and control algorithms.

Take the image of the entrepreneur as a driven accepter of risk, an individual (or set of individuals) hungry to amass a fortune as quickly as possible. This image is consistent with the traditional finance theory view of entrepreneurial startups, one that assumes that profit maximization is the firm’s sole motivation (Chaganti, DeCarolis & Deeds, 1995). Myers’s (1994) cost explanation of the pecking order hypothesis (i.e. entrepreneurs prefer internally generated funds first, debt next, and external equity last) incorporates this economically rational view of entrepreneurs’ financing preferences. According to this view, information asymmetry and uncertainty make the availability of external financing very limited and the cost of it prohibitively high. To compensate, entrepreneurs must give up greater and greater control in order to “buy” funds needed to achieve the desired growth and profitability. Indeed, Brophy and Shulman (1992, p. 65) state, “Those entrepreneurs willing to relinquish absolute independence in order to maximize expected shareholder wealth through corporate growth are deemed rational investors in the finance literature.” Undoubtedly, cost and availability explanations of financing choices are valid for many new and small businesses. However, many entrepreneurship researchers have long been dissatisfied with the incompleteness of this perspective.

The purpose of this study was to solve the problem of pose measurement of various parts for a precision assembly system.

A novel alignment method which can achieve high-precision pose measurement of microparts based on monocular microvision system was developed. To obtain the precise pose of parts, an area-based contour point set extraction algorithm and a point set registration algorithm were developed. First, the part positioning problem was transformed into a probability-based two-dimensional point set rigid registration problem. Then, a Gaussian mixture model was fitted to the template point set, and the contour point set is represented by hierarchical data. The maximum likelihood estimate and expectation-maximization algorithm were used to estimate the transformation parameters of the two point sets.

The method has been validated for accelerometer assembly on a customized assembly platform through experiments. The results reveal that the proposed method can complete letter-pedestal assembly and the swing piece-basal part assembly with a minimum gap of 10 µm. In addition, the experiments reveal that the proposed method has better robustness to noise and disturbance.

Owing to its good accuracy and robustness for the pose measurement of complex parts, this method can be easily deployed to assembly system.

The purpose of this paper is to present a surgical robot for spinal fusion and its control framework that provides higher operation accuracy, greater flexibility of robot position control, and improved ergonomics.

A human‐guided robot for the spinal fusion surgery has been developed with a dexterous end‐effector that is capable of high‐speed drilling for cortical layer gimleting and tele‐operated insertion of screws into the vertebrae. The end‐effector is position‐controlled by a five degrees‐of‐freedom robot body that has a kinematically closed structure to withstand strong reaction force occurring in the surgery. The robot also allows the surgeon to control cooperatively the position and orientation of the end‐effector in order to provide maximum flexibility in exploiting his or her expertise. Also incorporated for improved safety is a “drill‐by‐wire” mechanism wherein a screw is tele‐drilled by the surgeon in a mechanically decoupled master/slave system. Finally, a torque‐rendering algorithm that adds synthetic open‐loop high‐frequency components on feedback torque increases the realism of tele‐drilling in the screw‐by‐wire mechanism.

Experimental results indicated that this assistive robot for spinal fusion performs drilling tasks within the static regulation errors less than 0.1 μm for position control and less than 0.05° for orientation control. The users of the tele‐drilling reported subjectively that they experienced torque feedback similar to that of direct screw insertion.

Although the robotic surgery system itself has been developed, integration with surgery planning and tracking systems is ongoing. Thus, the screw insertion accuracy of a whole surgery system with the assistive robot is to be investigated in the near future.

The paper arguably pioneers the dexterous end‐effector appropriately designed for spinal fusion, the cooperative robot position‐control algorithm, the screw‐by‐wire mechanism for indirect screw insertion, and the torque‐rendering algorithm for more realistic torque feedback. In particular, the system has the potential of circumventing the screw‐loosening problem, a common defect in the conventional surgeon‐operated or robot‐assisted spinal fusion surgery.

The purpose of this study is solving the hand–eye calibration issue for line structured light vision sensor. Only after hand–eye calibration the sensor measurement data can be applied to robot system.

In this paper, the hand–eye calibration methods are studied, respectively, for eye-in-hand and eye-to-hand. Firstly, the coordinates of the target point in robot system are obtained by tool centre point (TCP), then the robot is controlled to make the sensor measure the target point in multiple poses and the measurement data and pose data are obtained; finally, the sum of squared calibration errors is minimized by the least square method. Furthermore, the missing vector in the process of solving the transformation matrix is obtained by vector operation, and the complete matrix is obtained.

On this basis, the sensor measurement data can be easily and accurately converted to the robot coordinate system by matrix operation.

This method has no special requirement for robot pose control, and its calibration process is fast and efficient, with high precision and has practical popularized value.

This study aims to investigate the moderating role of audit quality on the association between business group affiliation of firms and earnings management in the South Asian emerging economy of Bangladesh.

A usable sample of 917 firm-year observations was drawn from companies listed on the Dhaka Stock Exchange from 2005 to 2013. Data were collected from the annual reports of sample companies. Earnings management was measured using the absolute value of discretionary accruals, and two proxies were used to measure audit quality: auditor size and industry specialisation.

Results showed that the level of discretionary accruals is positively associated with business group affiliation status, and higher audit quality reduces this association. This suggests that in environments without strong investor protection, complex ownership structures create opportunities for controlling shareholders to expropriate minority shareholders. The controlling shareholders could then mask this practice through earnings management. The findings also show that in environments lacking strong investor protection, audit quality can help improve earnings quality for group-affiliated firms.

The results suggest that financial statement users need to consider audit quality for a reasonable evaluation of the earnings quality of business groups. The study also informs regulators by illuminating audit quality as a key area of focus in any effort directed at enhancing stock market efficiency through improved earnings quality in environments where business group affiliation is prevalent.

This study documents empirical evidence on the moderating effect of audit quality on the positive association between business group affiliation and earnings management.

This paper aims to present a pose correction method based on integrated virtual impedance control for avoiding collision and reducing impact.

The authors first constructed the artificial potential field (APF) considering the geometric characteristics of the end-effector. The characteristics of the proposed field were analyzed considering the position and orientation misalignment. Then, an integrated virtual impedance control was proposed by adding resultant virtual repulsive force into traditional impedance control. Finally, the authors modified a correction trajectory for avoiding collision and reducing impact with virtual force and contact force.

The APF the authors constructed can get rid of a local minimum. Comparing with linear correction, this method is able to avoid collision effectively. When the capturing target has intrinsic estimation error, the pose correction can ensure smooth transitions among different stages.

This method can be implemented on a manipulator with inner position control. It can be applied to an industrial robot with applications on robotic assembly for achieving a softer and smoother process. The method can also be expanded to the kind of claw-shaped end-effectors for capturing target.

As the authors know, it is the first time that the characteristics of the end-effector are considered for avoiding collision in capturing application. The proposed integrated virtual impedance control can provide smooth transitions among different stages without switching different force/position controllers.

Strong versions of the Precautionary Principle (PP) require regulators to prohibit or impose technology controls on activities that pose uncertain risks of possibly significant environmental harm. This decision rule is conceptually unsound and would diminish social welfare. Uncertainty as such does not justify regulatory precaution. While they should reject PP, regulators should take appropriate account of societal aversion to risks of large harm and the value of obtaining additional information before allowing environmentally risky activities to proceed.

This paper aims to improve the performance of a two-camera robotic feedback system designed for automatic pick and place application by modifying its velocity profile during switching of control.

Cooperation of global and local vision sensors ensures visibility of the target for a two-camera robotic system. The master camera, monitoring the workspace, guides the robot such that image-based visual servoing (IBVS) by the eye-in-hand camera transcends its inherent shortcomings. A hybrid control law steers the robot until the system switches to IBVS in a region proven for its asymptotic stability and convergence through a qualitative overview of the scheme. Complementary gain factors can ensure a smooth transition in velocity during switching considering the versatility and range of the workspace.

The proposed strategy is verified through simulation studies and implemented on a 6-DOF industrial robot ABB IRB 1200 to validate the practicality of adaptive gain approach while switching in a hybrid visual feedback system. This approach can be extended to any control problem with uneven switching surfaces or coarse/fine controllers which are subjected to discrete time events.

In complex workspace where robots operate in parallel with other robots/humans and share workspaces, the supervisory control scheme ensures convergence. This study proves that hybrid control laws are more effective than conventional approaches in unstructured environments and visibility constraints can be overcome by the integration of multiple vision sensors.

The supervisory control is designed to combine the visual feedback data from eye-in-hand and eye-to-hand sensors. A gain adaptive approach smoothens the velocity characteristics of the end-effector while switching the control from master camera to the end-effector camera.