Background/Purpose. This three-dimensional finite element study observed the stress distribution characteristics of 12 types of dental implants and their surrounding bone tissues with various structured abutments, implant threads, and healing methods under different amounts of concentrated loading.Materials and Methods. A three-dimensional geometrical model of a dental implant and its surrounding bone tissue was created; the model simulated a screw applied with a preload of 200 N or a torque of 0.2 N·m and a prosthetic crown applied with a vertical or an inclined force of 100 N. The Von Mises stress was evaluated on the 12 types of dental implants and their surrounding bone tissues.Results. Under the same loading force, the stress influence on the implant threads was not significant; however, the stress influence on the cancellous bone was obvious. The stress applied to the abutment, cortical bone, and cancellous bone by the inclined force applied to the crown was larger than the stress applied by the vertical force to the crown, and the abutment stress of the nonsubmerged healing implant system was higher than that of the submerged healing implant system.Conclusion. A dental implant system characterised by a straight abutment, rectangle tooth, and nonsubmerged healing may provide minimum value for the implant-bone interface.

In this paper, we try to show the state of the art on the formation control of multiple quadrotors. From the literature, we summarize some most interested issues such as potential applications, representation of multiple quadrotor formation, consensus, formation control, formation configurations, localization, etc. According to these research, we point out the difficulties and the tendency of research in the field of multiple quadrotors control.

Aiming at the problems of “local minimum” and “unreachable target” existing in the traditional artificial potential field method in path planning, an improved artificial potential field method was proposed after analyzing the fundamental causes of the above problems. The method solved the problem of local minimum by modifying the direction and influence range of the gravitational field, increasing the virtual target and evaluation function, and the problem of unreachable targets is solved by increasing gravity. In view of the change of motion state of robot fish in amphibious environments, the improved artificial potential field method was fused with a dynamic window algorithm, and a dynamic window evaluation function of the optimal path was designed on the basis of establishing the dynamic equations of land and underwater. Then, the simulation experiment was designed under the environment of Matlab2019a. Firstly, the improved and traditional artificial potential field methods were compared. The results showed that the improved artificial potential field method could solve the above two problems well, shorten the operation time and path length, and have high efficiency. Secondly, the influence of different motion modes on path planning is verified, and the result also reflects that the amphibious robot can avoid obstacles flexibly and reach the target point accurately according to its own motion ability. This paper provides a new way of path planning for the amphibious robot.

The seam tracking operation is essential for extracting welding seam characteristics which can instruct the motion of a welding robot along the welding seam path. The chief tasks for seam tracking would be divided into three partitions. First, starting and ending points detection, then, weld edge detection, followed by joint width measurement, and, lastly, welding path position determination with respect to welding robot co-ordinate frame. A novel seam tracking technique with a four-step method is introduced. A laser sensor is used to scan grooves to obtain profile data, and the data are processed by a filtering algorithm to smooth the noise. The second derivative algorithm is proposed to initially position the feature points, and then linear fitting is performed to achieve precise positioning. The groove data are transformed into the robot’s welding path through sensor pose calibration, which could realize real-time seam tracking. Experimental demonstration was carried out to verify the tracking effect of both straight and curved welding seams. Results show that the average deviations in the X direction are about 0.628 mm and 0.736 mm during the initial positioning of feature points. After precise positioning, the average deviations are reduced to 0.387 mm and 0.429 mm. These promising results show that the tracking errors are decreased by up to 38.38% and 41.71%, respectively. Moreover, the average deviations in both X and Z direction of both straight and curved welding seams are no more than 0.5 mm, after precise positioning. Therefore, the proposed seam tracking method with four steps is feasible and effective, and provides a reference for future seam tracking research.

The welding seam tracking operation ensures that the welding torch of the welding robot can go with the welding seam during the whole symmetrical robotic welding procession. To achieve three-dimensional complex welding seams tracking, a four-step welding seam tracking system is suggested based on segmented scanning, combined filtering, feature-point extraction, and welding path planning. From using the laser sensor installed at the end of welding robot, the welding seam data was continuously collected in multiple segments by segmented scanning. For the purpose of improving seam tracking accuracy, a combined filtering technique was used to correct the data to reduce the effects of burrs, data distortion, and noise on the surface of the weldment. Then, the feature points were collected so that the coordinate system will be calibrated to identify the welding points. Finally, a spatial welding path was obtained by welding path planning. Experimental investigations of the two-dimensional (2D) symmetrical S-shaped and three-dimensional (3D) curved welding seams were conducted. The obtained results demonstrate the proposed method can form a complete welding path. The average errors of the two weldments are about 0.296 mm and 0.292 mm, respectively. This shows that the proposed tracking method is effective and can provide a reference for the research of high-precision seam tracking and automatic welding.

Robot dynamics and its parameter identification are of great significance to the realization of optimal control and human–machine interaction. The objective of this research is to address the shortcomings of establishing and identifying the self-developed six-degree-of-freedom (6-DoF) collaborative robot dynamics, which leads to a large error in the predicted torque of the proposed robot. A long short-term memory (LSTM) in an optimized recurrent neural network (RNN) is proposed to compensate the dynamic model of the proposed 6-DoF collaborative robot based on the consideration of gravity, Coriolis force, inertial force, and friction force. The analysis and experimental findings provide promising results. The compensated collaborative robot dynamic model based on LSTM in an optimized RNN displays a good prediction on the actual torque, and the root-mean-square (RMS) error between predicted and actual torques are reduced by 61.8% to 78.9% compared to the traditional dynamic model. Results of the experimental applications demonstrate the validity of the proposed systematic error compensation strategy.