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To paint large workpieces automatically, painting manipulators with hollow wrists must be transported by mobile platforms to different positions because of their limited workspaces. This paper aims to provide a visualization method for finding appropriate base positions (BPs) and maximum painting areas for manipulators.

This paper begins by analyzing the motion characteristics of manipulators possessing a spherical wrist and summarizing them into three constraints – positioning, orientation and singularity avoidance. The hollow wrist is simplified and considered as spherical by introducing the concepts of an inner wrist center and an outer wrist center. Taking the three constraints into consideration, the boundaries of the manipulating space are formulated analytically. Finally, to verify the method, the space obtained is applied to determine the maximum painting areas for flat, cylindrical and conical surfaces. Experiments of robotic painting were used to confirm the results.

Compared with previous studies, the maximum areas obtained using the proposed method increased by 17-131 per cent with an algorithm of lower complexity, and the process remained visually intuitive, thereby demonstrating that the method of manipulating space is more effective.

Such a method allows individuals to visualize the entire painting area at the current BP, thereby maximizing painting areas or optimizing BPs. It opens a black box that is the relationship between BPs and blocks. The method can also be used to choose the best configuration for painting manipulators, select the end-effector structure parameters, split surfaces into blocks, etc.

This paper aims to achieve automatically surface segmentation for painting different kinds of aircraft efficiently considering the demands of painting robot.

This project creatively proposed one method that accepts point cloud, outputs several blocks, each of which can be handled by ABB IRB 5500 in one station. Parallel PointNet (PPN) is proposed in this paper for better handling six dimensional aircraft data including every point normal. Through semantic segmentation of PPN, each surface has its own identity information indicating which part this surface belongs to. Then clustering considering constraints is applied to complete surface segmentation with identity information. To guarantee segmentation paintable and improve painting efficiency, different dexterous workspaces of IRB 5500 corresponding to different postures have been analyzed carefully.

The experiments confirm the effectiveness of the proposed surface segmentation method for painting different types of aircraft by IRB 5500. For semantic segmentation on aircraft data with point normal, PPN has higher precision than PointNet. In addition, the whole algorithm can efficiently segment one complex aircraft into qualified blocks, each of which has its own identity information, can be painted by IRB 5500 in one station and has fewer edges with other blocks.

As the provided experiments indicate, the proposed method can segment one aircraft into qualified blocks automatically, which highly improves the efficiency in aircraft painting compared with traditional approaches. Moreover, the proposed method is able to provide identity information of each block, which is necessary for application of different paint parameters and different paint materials. In addition, final segmentation results by the proposed method behaves better than k-means cluster on variance of normal vector distance.

Inspired by semantic segmentation of 3 D point cloud, some improvements based on PointNet have been proposed for better handling segmentation of 6 D point cloud. By introducing normal vectors, semantic segmentation could be accomplished precisely for close points with opposite normal, such as wing upper and lower surfaces. Combining deep learning skills with traditional methods, the proposed method is proved to behave much better for surface segmentation task in aircraft painting.

The purpose of this paper is to determine the base position and the largest working area for mobile manipulators. The base position determines the workspace of the mobile manipulator, particularly when the operation mode is intermittent (i.e. the mobile platform stops when the manipulator conducts the task). When the base of the manipulator is in the intersection area of the Base’s Workable Location Spaces (BWLSes), the end effector (EE) can reach all path points. In this study, the intersection line of BWLSes is calculated numerically, and the largest working area is determined using the BWLS concept. The performance of this method is validated with simulations on specific surface segments, such as plane, cylinder and conical surface segments.

The BWLS is used to determine the largest working area and the base position in which the mobile manipulator can reach all path points with the objective of reducing off-line planning time.

Without considering the orientation of the EE, the base position and the working area for the mobile manipulator are determined using the BWLS. Compared to other methods, the proposed algorithm is beneficial when the planning problem has six dimensions, ensuring the reachability and stability of the EE.

The algorithm needs no manual configuration, and its performance is investigated for typical surfaces in practical applications.

The purpose of this paper is to design a special automatic redundant robot painting system (RRPS), which can automatically navigate and paint in the long non-regular duct.

The RRPS is designed with three subsystems: a redundant robot, a spraying system and a control and safety system. Based on the modular design theory, the robot falls naturally into a mobile platform, a 4-DOF location mechanism and a 10-DOF manipulator. The restriction of the distance between the links and the duct axis is used to plan the trajectory of the manipulator so that it would not collide with the duct. The restriction model is constructed by minimizing the sum of the weighed distances between the duct axis and the special points.

A fully working prototype system has been developed. Test results show that the minimal distance between the robot joints and duct is 18 mm, and it can finish painting long non-regular ducts at the speed of 12.5 cm/s and the spraying distance of 16 cm. The quality of coating layers is good.

The RRPS was used to paint non-regular rectangular ducts, cylindrical ducts and long non-regular ducts. The feasibility of painting long non-regular duct is proved with the prototype implementation and successful test results.

The RRPS shows a novel solution that is based on the 14-DOF redundant robot design for painting long non-regular ducts which is used in airplane.

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.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

The purpose of this paper is to present a vision-based method for the kinematic calibration of a six-degrees-of-freedom parallel robot named Hexa using only one Universal Serial Bus (USB) camera and a chess pattern installed on the robot's mobile platform. Such an approach avoids using any internal sensors or complex three-dimensional measurement systems to obtain the pose (position/orientation) of the robot's end-effector or the joint coordinates.

The setup of the proposed method is very simple; only one USB camera connected to a laptop computer is needed and no contact with the robot is necessary during the calibration procedure. For camera modeling, a pinhole model is used; it is then modified by considering some distortion coefficients. Intrinsic and extrinsic parameters and the distortion coefficients are found by an offline minimization algorithm. The chess pattern makes image corner detection very straightforward; this detection leads to finding the camera and then the kinematic parameters. To carry out the calibration procedure, several trajectories are run (the results of two of them are presented here) and sufficient specifications of the poses (positions/orientations) are calculated to find the kinematic parameters of the robot. Experimental results obtained when applying the calibration procedure on a Hexa parallel robot show that vision-based kinematic calibration yields enhanced and efficient positioning accuracy. After successful calibration and addition of an appropriate control scheme, the robot has been considered as a color-painting prototype robot to serve in relevant industries.

Experimental results obtained when applying the calibration procedure on a Hexa parallel robot show that vision-based kinematic calibration yields enhanced and efficient positioning accuracy.

The enhanced results show the advantages of this method in comparison with the previous calibration methods.

The purpose of this paper is to present the results obtained in the field tests of a new system for detection and location of antipersonnel land mines.

The paper presents briefly the overall system and then it focuses on the description and analysis of the results obtained in three basic experiments: accuracy for following trajectories, mine detection and capability for walking over landmines.

The paper finds that the system has been assessed positively for this specific application because it satisfies the initial system requirements.

The research and experiments have been focused on irregular terrain with low vegetation and free from obstacles. Further research will be focused on the complete coverage of a terrain including large vegetation and obstacles.

This paper presents practical results for a very well defined application: humanitarian de‐mining. However, many of the results related with robot location, following of trajectories and general control techniques are applicable to any mobile robot for outdoor applications in general.

This paper is the first work (to the best author's knowledge) reporting experimental features of a walking system for humanitarian de‐mining. The paper does not only report on the mobile platform, but also on the scanning manipulator and sensor head features.

The purpose of this paper is to design the localization and tracking algorithms for our mobile welding robot to carry out the large steel structure welding operations in industrial environment.

Extended Kalman filter, considering the bicycle-modeled robot, is adopted in the localization algorithm. The position and orientation of our mobile welding robot is estimated using the feedback of the laser sensor and the robot motion commands history. A backstepping variable is involved in the tracking algorithm. By introducing a specifically selected Lyapunov function, we proved the tracking algorithm using Barbalat Lemma, which leads the errors of estimated robot states to converge to zero.

The experiments show that the proposed localization method is fast and accurate and the tracking algorithm is robust to track straight lines, circles and other typical industrial curve shapes. The proposed localization and tracking algorithm could be used, but not limited to the mobile welding.

Localization problem which is neglected in previous research is very important in mobile welding. The proposed localization algorithm could estimate the robot states timely and accurately, and no additional sensors are needed. Furthermore, using the estimated robot states, we proposed and proved a tracking algorithm for bicycle-modeled mobile robots which could be used in welding as well as other industrial operation scenarios.

This paper aims to propose a new view planning method which can be used to calculate the next-best-view (NBV) for multiple manipulators simultaneously and build an automated three-dimensional (3D) object reconstruction system, which is based on the proposed method and can adapt to various industrial applications.

The entire 3D space is encoded with octree, which marks the voxels with different tags. A set of candidate viewpoints is generated, filtered and evaluated. The viewpoint with the highest score is selected as the NBV.

The proposed method is able to make the multiple manipulators, equipped with “eye-in-hand” RGB-D sensors, work together to accelerate the object reconstruction process.

Compared to the existed approaches, the proposed method in this paper is fast, computationally efficient, has low memory cost and can be used in actual industrial productions where the multiple different manipulators exist. And, more notably, a new algorithm is designed to speed up the generation and filtration of the candidate viewpoints, which can guarantee both speed and quality.