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It is essential to level the drilling platform across which a drilling robot travels in a slant underground coal mine tunnel to ensure smooth operation of the drill rod. However, existing leveling methods do not provide dynamic performance under the drilling conditions of the underground coal mine. A four-point dynamic leveling algorithm is presented in this paper based on the platform attitude and support rod displacement (DLAAD). An experimental drilling robot demonstrates its dynamic leveling capability and ability to ensure smooth drill rod operations.

The attitude coordinate of the drilling robot is established according to its structure. A six-axis combined sensor is adopted to detect the platform attitude, thus revealing the three-axis Euler angles. The support rod displacement values are continuously detected by laser displacement sensors to obtain the displacement increment of each support rod as needed. The drilling robot is leveled according to the current support rod displacement and three-dimensional (3 D) attitude detected by the six-axis combined sensor dynamically.

Experimental results indicate that the DLAAD algorithm is correct and effectively levels the drilling platform dynamically. It can thus provide essential support in resolving drill rod sticking problems during actual underground coal mine drilling operations.

The DLAAD algorithm supports smooth drill rod operations in underground coal mines, which greatly enhances safety, reduces power consumption, and minimizes cost. The approach proposed here thus represents considerable benefits in terms of coal mine production and shows notable potential for application in similar fields.

The novel DLAAD algorithm and leveling control method are the key contributions of this work, they provide dynamical 3 D leveling and help to resolve drill rod sticking problems.

Six-axis force sensors play an important role in civilian and military fields because of their multifunctionality. In the context of sensor structure design, sensitivity and sensitivity isotropy are often considered. This paper aims to study the possible relationship between the sensitivity/sensitivity isotropy and structural parameters of an 8/4–4 parallel six-axis force sensor. A comprehensive evaluation index and structural optimization design scheme are suggested in the end.

Based on the conditional number of the Jacobian matrix spectral norm, the sensitivity and sensitivity isotropy of the sensor are derived. Orthogonal experiments are used to determine the degree of primary and secondary factors that have a substantial effect on the sensor characteristics. The relationship between the performance indices and the structural parameters is analyzed by the performance atlas method. The comprehensive evaluation index lays the foundation for the structural optimization design of an 8/4–4 parallel six-axis force sensor.

The variation in each performance index of the sensor for each of the structural parameters is analyzed, and the structural parameters of the sensor with the desired performance indices can be easily selected from the performance atlases. A comprehensive performance evaluation index with a target value of 1 is proposed, and the overall influence of the structural parameters on the sensor performance index is investigated. A simulation example shows the feasibility of the proposed evaluation index.

The importance of each structural parameter of the 8/4–4 parallel six-axis force sensor is determined through orthogonal experiments in this paper. Relations among the structural parameters meeting the performance indices are derived and shown in the performance atlases. A comprehensive evaluation index is proposed to analyze the overall sensor performance.

This paper aims to propose a set of six-axis robot arm welding seam tracking experiment platform based on Halcon machine vision library to resolve the curve seam tracking issue.

Robot-based and image coordinate systems are converted based on the mathematical model of the three-dimensional measurement of structured light vision and conversion relations between robot-based and camera coordinate systems. An object tracking algorithm via weighted local cosine similarity is adopted to detect the seam feature points to prevent effectively the interference from arc and spatter. This algorithm models the target state variable and corresponding observation vector within the Bayes framework and finds the optimal region with highest similarity to the image-selected modules using cosine similarity.

The paper tests the approach and the experimental results show that using metal inert-gas (MIG) welding with maximum welding current of 200A can achieve real-time accurate curve seam tracking under strong arc light and splash. Minimal distance between laser stripe and welding molten pool can reach 15 mm, and sensor sampling frequency can reach 50 Hz.

Designing a set of six-axis robot arm welding seam tracking experiment platform with a system of structured light sensor based on Halcon machine vision library; and adding an object tracking algorithm to seam tracking system to detect image feature points. By this technology, this system can track the curve seam while welding.

The purpose of this study is to design a spherical sensor which can detect the surge from various directions to lay the foundation of the research of surge.

This paper designed a spherical sensor to detect the impact force generated by the surge. To realize the depth and stability control of the shallow underwater vehicles, it is necessary to do research and analysis on the surge in shallow waters. The spherical sensor with novel structure was skillfully composed of 24 cantilever beam pressure-type strain sensors. It is powerful to detect the surge from various directions simultaneously.

It is proved that the spherical sensor can accurately collect the surge data from multiple directions through experiments, which laid the foundation of the anti-surge study.

Surge is not a new topic. But there is no effective tool to detect surge. The research of this paper is an attempt to provide an available tool to analyze surge. The research limitation is that the pool where the spherical sensor is installed is a little small. In the future, a bigger pool can be used.

A deep and comprehensive analysis of surge can be conducted according to the surge data detected by the spherical sensor to achieve the essential features of surge. This lays the foundation for the accurate control of Autonomous Underwater Vehicles (AUVs), especially fixed depth and stability control.

As the control accuracy of AUVs increases, the AUVs can perform much more difficult tasks such as port monitoring, underwater salvaging, underwater pipeline maintenance and so on. These can be applied in commercial applications or in the national defense of many countries.

A novel spherical sensor using 24 cantilever beam pressure-type strain sensors to detect the surge was designed. The spherical sensor was installed in the physical surge simulator to collect surge data and conduct an analysis of the collected data.

Existing robot-assisted minimally invasive surgery (RMIS) system lacks of force feedback, and it cannot provide the surgeon with interaction forces between the surgical instruments and patient’s tissues. This paper aims to restore force sensation for the RMIS system and evaluate effect of force sensing in a master-slave manner.

This paper presents a four-DOF surgical instrument with modular joints and six-axis force sensing capability and proposes an incremental position mode master–slave control strategy based on separated position and orientation to reflect motion of the end of master manipulator to the end of surgical instrument. Ex-vivo experiments including tissue palpation and blunt dissection are conducted to verify the effect of force sensing for the surgical instrument. An experiment of trajectory tracking is carried out to test precision of the control strategy.

Results of trajectory tracking experiment show that this control strategy can precisely reflect the hand motion of the operator, and the results of the ex-vivo experiments including tissue palpation and blunt dissection illustrate that this surgical instrument can measure the six-axis interaction forces successfully for the RMIS.

This paper addresses the important role of force sensing and force feedback in RMIS, clarifies the feasibility to apply this instrument prototype in RMIS for force sensing and provides technical support of force feedback for further clinical application.

This study aims to introduce a multi-configuration, three-finger dexterous hand with integrated high-dimensional sensors and provides an analysis of its design, modeling and kinematics.

A mechanical design scheme of the three-finger dexterous hand with a reconfigurable palm is proposed based on the existing research on dexterous hands. The reconfigurable palm design enables the dexterous hand to achieve four grasping modes to adapt to multiple grasping tasks. To further enhance perception, two six-axis force and torque sensors are integrated into each finger. The forward and inverse kinematics equations of the dexterous hand are derived using the D-H method for kinematics modeling, thus providing a theoretical model for index analysis. The performance is evaluated using three widely applied indicators: workspace, interactivity of fingers and manipulability.

The results of kinematics analysis show that the proposed hand has excellent dexterity. Additionally, three different experiments are conducted based on the proposed hand. The performance of the dexterous hand is also verified by fingertip force, motion accuracy test, grasping and in-hand manipulation experiments based on Feix taxonomy. The results show that the dexterous hand has good grasping ability, reproducing 82% of the natural movement of the human hand in daily grasping activities and achieving in-hand manipulations such as translation and rotation.

A novel three-finger dexterous hand with multi-configuration and integrated high-dimensional sensors is proposed. It performs better than the previously designed dexterous hand in actual experiments and kinematic performance analysis.

In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping.

This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target.

In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained.

The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.

This paper aims to illustrate the growing role of robots in the electronics industries.

Following a short introduction, this paper discusses robotic applications and products in three sectors of the electronics industry: semiconductor processing, printed circuit manufacture and electronic product assembly. Finally, conclusions are drawn.

The major application in semiconductor manufacture is the handling of silicon wafers during both front- and back-end processes and products include cleanroom certified multi-axis robotic arms, some mounted on mobile platforms, and automated guided vehicles. Applications in printed circuit board production include component handling and insertion, soldering, inspection, testing and packing. These exploit Cartesian, SCARA and six-axis articulated robots and cobots play an important role where automated and manual processes operate in close proximity. Electronic product assembly applications include part handling, soldering, bonding and sealing, screw driving, test and inspection and packaging. Cobots offer the benefits of a small footprint which allows deployment in the often limited space and use in proximity to humans. As yet, robotic assembly of complex electronic products such as smartphones and computers has not been realised for technical reasons.

This study provides a detailed review of robotic products and applications in three key sectors of the electronics industries.

Many companies develop vision systems, but ultrasonics is now being used for some applications. John Hartley describes an unusual force‐sensing system from Hitachi.

The emergence of smart wearables using clothing as a technology platform is a significant milestone with considerable implications for industrial convergence, creating new value for fashion. This paper aimed to present a premeditated prototype to integrate a human activity recognition (HAR) system into outdoor clothing.

For the development of wearable HAR (WHAR) clothing, this paper explored three subject areas: fashion design related to the structural feature of the clothing platform, electronics related to wearable circuits and modules design and graphic user interface design related to smartphone application development.

For WHAR functions in outdoor terrains, the coexistence of accelerometer–gyroscope sensing and distance-sensing could be practical to surpass the technological limitation of activity and posture recognition with gyro sensors highly depending on the changes of acceleration and angles.

Through the vital sign check and physical activity–change recognition function, this study's WHAR system allows users to check their health by themselves and avoid overwork. A quick rescue is possible manually and automatically in a dangerous situation by notifying others. Thus, it can help protect users' health and safety (life).

This study designed the modularization of HAR functions generally installed in indoor medical spaces. Through the approach, smart clothing–embracing WHAR systems optimized for health and safety care for outdoor environments was pursued to diversify expensive roles of clothing for technological applications.