Industrial Robot最新文献

Purpose

The aim of this article is to provide details of recent technological developments in robotic teleoperation.

Design/methodology/approach

Following a short introduction, the two main sections of this article provide examples of recent research involving the application of virtual reality and haptic technologies, respectively, to robotic teleoperation. Brief conclusions are drawn.

Findings

Teleoperation systems are being developed which incorporate virtual reality and haptic feedback technologies. Those using virtual reality seek to enhance the operator’s feeling of immersion in the scene and improve their situation awareness and trials involving diverse tasks illustrate that the technology can achieve these aims and overcome many limitations of traditional systems. Haptic feedback further enhances the degree of operator involvement and control and is now being adopted in commercial minimally invasive surgical systems. Systems which combine virtual reality with haptic feedback are being developed and have the potential to allow operators to conduct increasingly complex tasks.

Originality/value

Through reference to recent research, this illustrates how virtual reality and haptic technologies are enhancing the capabilities of robotic teleoperation.

Purpose

Regular cable trench inspection is crucial, and robotics automation provides an efficient and safer alternative to manual labor. However, existing robots have limited capabilities in traversing obstacles and lack a mechanical arm for detecting cables and equipment. This study aims to develop an intelligent robot for cable trench inspection, enhancing obstacle-crossing abilities and incorporating a mechanical arm for inspection tasks.

Design/methodology/approach

This study presents an intelligent robot for cable trench inspection, featuring a six-degree-of-freedom mechanical arm mounted on a six-track chassis with four flippers. The robot's climbing and obstacle-crossing stability, as well as the motion range of the mechanical arm, are analyzed. The positioning, navigation and remote monitoring systems are developed. Experiments, including climbing and obstacle-crossing performance tests, along with navigation and positioning system tests, are conducted. Finally, the robot's practicability is verified through field testing.

Findings

Equipped with flipper tracks, the cable trench inspection robot can traverse obstacles up to 30 cm high and maintain stable locomotion on 30° slopes. Its navigation system enables autonomous operation, while the mechanical arm performs cable current detection tasks. The remote monitoring system provides comprehensive control of the robot and environmental parameter monitoring in cable trenches.

Originality/value

The front and rear flipper tracks enhance the robot's ability to traverse obstacles in cable trenches. The mechanical arm addresses cable current and equipment contact detection issues. The navigation and remote monitoring systems improve the robot's autonomous operation and environmental monitoring capabilities. Implementing this robot can advance the automation and intelligence of cable trench inspections.

Purpose

This paper aims to present a new trajectory scheduling method to generate a smooth and continuous trajectory for a hybrid machining robot.

Design/methodology/approach

The trajectory scheduling method includes two steps. First, a G3 continuity local smoothing approach is proposed to smooth the toolpath. Then, considering the tool/joint motion and geometric error constraints, a jerk-continuous feedrate scheduling method is proposed to generate the trajectory.

Findings

The simulations and experiments are conducted on the hybrid robot TriMule-800. The simulation results demonstrate that this method is effectively applicable to machining trajectory scheduling for various parts and is computationally friendly. Moreover, it improves the robot machining speed and ensures smooth operation under constraints. The results of the S-shaped part machining experiment show that the resulting surface profile error is below 0.12 mm specified in the ISO standard, confirming that the proposed method can ensure the machining accuracy of the hybrid robot.

Originality/value

This paper implements an analytical local toolpath smoothing approach to address the non-high-order continuity problem of the toolpath expressed in G code. Meanwhile, the feedrate scheduling method addresses the segmented paths after local smoothing, achieving smooth and continuous trajectory generation to balance machining accuracy and machining efficiency.

Purpose

This study aims to improve the stability and obstacle surmounting ability of the traditional wall-climbing robot on the surface of the ship, a wheel-track composite magnetic adsorption wall-climbing robot is proposed in this paper.

Design/methodology/approach

The robot adopts a front and rear obstacle-crossing mechanism to achieve a smooth crossover. The robot is composed of two passive obstacle-crossing mechanisms and a frame, which is composed of two obstacle-crossing magnetic wheels and a set of tracks. The obstacle-crossing is realized by the telescopic expansion of the obstacle-crossing mechanism. Three static failure models are established to determine the minimum adsorption force for the robot to achieve stable motion. The Halbach array is used to construct the track magnetic circuit, and the influence of gap, contact area and magnet thickness on the adsorption force is analyzed by parameter simulation.

Findings

The prototype was designed and manufactured by the authors for static failure and obstacle crossing tests. The prototype test results show that the robot can cross the obstacle of 10 mm height under the condition of 20 kg load.

Originality/value

A new structure of wall-climbing robot is proposed and verified. According to the test results, the wall-climbing robot can stably climb over the obstacle of 10 mm height under the condition of 20 kg load, which provides a new idea for future robot design.

Purpose

This paper proposes a self-supervised monocular depth estimation algorithm under multiple constraints, which can generate the corresponding depth map end-to-end based on RGB images. On this basis, based on the traditional visual simultaneous localisation and mapping (VSLAM) framework, a dynamic object detection framework based on deep learning is introduced, and dynamic objects in the scene are culled during mapping.

Design/methodology/approach

Typical SLAM algorithms or data sets assume a static environment and do not consider the potential consequences of accidentally adding dynamic objects to a 3D map. This shortcoming limits the applicability of VSLAM in many practical cases, such as long-term mapping. In light of the aforementioned considerations, this paper presents a self-supervised monocular depth estimation algorithm based on deep learning. Furthermore, this paper introduces the YOLOv5 dynamic detection framework into the traditional ORBSLAM2 algorithm for the purpose of removing dynamic objects.

Findings

Compared with Dyna-SLAM, the algorithm proposed in this paper reduces the error by about 13%, and compared with ORB-SLAM2 by about 54.9%. In addition, the algorithm in this paper can process a single frame of image at a speed of 15–20 FPS on GeForce RTX 2080s, far exceeding Dyna-SLAM in real-time performance.

Originality/value

This paper proposes a VSLAM algorithm that can be applied to dynamic environments. The algorithm consists of a self-supervised monocular depth estimation part under multiple constraints and the introduction of a dynamic object detection framework based on YOLOv5.

Purpose

The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment requirements of deep learning methods on dexterous hands.

Design/methodology/approach

A distributed control architecture was designed, comprising embedded motion control subsystems and a host control subsystem built on ROS. The design of embedded controller state machines and clock synchronization algorithms ensured the stable operation of the entire distributed control system.

Findings

Experiments demonstrate that the entire system can operate stably at 1KHz. Additionally, the host can accomplish learning-based estimates of contact position and force.

Originality/value

This distributed architecture provides foundational support for the large-scale application of machine learning algorithms on dexterous hands. Dexterity hands utilizing this architecture can be easily integrated with robotic arms.

Purpose

The purpose of this study is to address the welding demands within large steel structures by presenting a global spatial motion planning algorithm for a mobile manipulator. This algorithm is based on an independently developed wall-climbing robot, which comprises a four-wheeled climbing mobile platform and a six-degree-of-freedom robotic manipulator, ensuring high mobility and operational flexibility.

Design/methodology/approach

A convex hull feasible domain constraint is developed for motion planning in the mobile manipulator. For extensive spatial movements, connected sequences of convex polyhedra are established between the composite robot’s initial and target states. The composite robot’s path and obstacle avoidance optimization problem are solved by constraining the control points on B-spline curves. A dynamic spatial constraint rapidlye-xploring random trees-connect (RRTC) motion planning algorithm is proposed for the manipulator, which quickly generates reference paths using spherical spatial constraints at the manipulator’s end, eliminating the need for complex nonconvex constraint modeling.

Findings

Experimental results show that the proposed motion planning algorithm achieves optimal paths that meet task constraints, significantly reducing computation times in task conditions and shortening operation times in non-task conditions.

Originality/value

The algorithm proposed in this paper holds certain application value for the realization of automated welding operations within large steel structures using mobile manipulator.

Purpose

This paper aims to introduce a wheeled vehicle robot for adapting to the surface terrain of the 500-m diameter reflector of the FAST radio telescope in China.

Design/methodology/approach

By analyzing vehicles applied for different off-road environments, a six-wheeled architecture with a passive “triple-bogie” suspension is selected. A subscale model of the vehicle robot is designed, along with statics modeling and multibody simulations of the dynamics on simulated reflector panel surfaces. The slope- and step-climbing abilities of the subscale vehicle are discussed in accordance with numerical and experimental tests. An engineering scale vehicle is subsequently manufactured and tested on surface terrains of lateral as well as vertical gaps, and is finally validated on the FAST reflector.

Findings

This model of vehicle robot exhibits strong structure stability under desired payload. It can stably cross lateral gaps for maximum surface slope 28° and can traverse vertical gap for maximum surface slope 23°. The traversing abilities satisfy the mobility requirements subjected to surface terrains of FAST reflector.

Originality/value

The engineering vehicle robot negotiates the lateral as well as vertical gaps between triangle panels and has been successfully applied to the FAST reflector serving for inspection and maintenance work.

Purpose

This study comprehensively reviews the Fourth Industrial Revolution, which refers to Industry 4.0 (IR 4.0) applications in small and medium enterprises (SMEs). Multinational companies and big corporations have the capacity and resources to implement IR 4.0, but SMEs are limited due to financial constraints, expertise and lack of resources. Even so, IR 4.0 is required as technologies evolve and market demand has changed how firms do business.

Design/methodology/approach

To uncover the potential of IR 4.0 and critical determinants of SMEs’ adoption of IR 4.0, this study presents a bibliometric analysis to evaluate the current research streams in IR 4.0 adoption among SMEs through bibliographic coupling. Furthermore, this review provides a glimpse of the future by analyzing prospective trends on IR 4.0 in SMEs.

Findings

Bibliographic coupling produces five clusters: (1) challenges and barriers in IR 4.0 implementation among SMEs, (2) technological adoption of IR 4.0, (3) opportunities and benefits of IR 4.0, (4) business model innovation and (5) implication of IR 4.0 on SMEs technologies. On the contrary, co-word analysis produces three clusters: (1) technologies in IR 4.0, (2) strategy and management of IR 4.0 among SMEs and (3) IR 4.0 model for SMEs.

Research limitations/implications

Implications are directly related to business owners, policymakers and technology developers meeting the needs of the industry and SMEs, which are the focus of this review.

Originality/value

The findings contribute significantly to the body of knowledge by presenting a state-of-the-art science mapping approach to uncover the knowledge structure and intellectual linkage of IR 4.0 adoption within SMEs.

Purpose

Dynamically tracking the target by unmanned ground vehicles (UGVs) plays a critical role in mobile drone recovery. This study aims to solve this challenge under diverse random disturbances, proposing a dynamic target tracking framework for UGVs based on target state estimation, trajectory prediction, and UGV control.

Design/methodology/approach

To mitigate the adverse effects of noise contamination in target detection, the authors use the extended Kalman filter (EKF) to improve the accuracy of locating unmanned aerial vehicles (UAVs). Furthermore, a robust motion prediction algorithm based on polynomial fitting is developed to reduce the impact of trajectory jitter caused by crosswinds, enhancing the stability of drone trajectory prediction. Regarding UGV control, a dynamic vehicle model featuring independent front and rear wheel steering is derived. Additionally, a linear time-varying model predictive control algorithm is proposed to minimize tracking errors for the UGV.

Findings

To validate the feasibility of the framework, the algorithms were deployed on the designed UGV. Experimental results demonstrate the effectiveness of the proposed dynamic tracking algorithm of UGV under random disturbances.

Originality/value

This paper proposes a tracking framework of UGV based on target state estimation, trajectory prediction and UGV predictive control, enabling the system to achieve dynamic tracking to the UAV under multiple disturbance conditions.