A review of emerging industry 4.0 technologies in remanufacturing

Physiological temperature varies temporally and spatially Accurate and real-time detection of localized temperature changes in biological tissues regardless of large deformation is crucial to understand thermal principle of homeostasis, to assess sophisticated health conditions, and further to offer possibilities of building a smart healthcare and medical system Additionally, continuous temperature mapping in flexible and stretchable formats opens up many other potential areas, such as artificially electronic skins and reflection of emotional changes This review exploits a comprehensive investigation onto recent advances in flexible temperature sensors, stretchable sensor networks, and platforms constructed in soft and compliant formats for wearable physiological monitoring The most recent examples of flexible temperature sensors are first discussed regarding to their materials, structures, electrical and mechanical properties; temperature sensing network technologies in new materials and structural designs are then presented based on platforms comprised of multiple physical sensors and stretchable electronics Finally, wearable applications of the sensing network are described, such as detection of human activities, monitoring of health conditions, and emotion-related bodily sensations Conclusions are made with emphasis on critical issues and new trends in the field of wearable temperature sensor network technologies

Review of Flexible Temperature Sensing Networks for Wearable Physiological Monitoring

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

https://www.mdpi.com/1424-8220/18/2/571/pdf

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

In recent years, topics related to robotics have become one of the researching fields. In the meantime, intelligent mobile robots have great acceptance, but the control and navigation of these devices are very difficult, and the lack of dealing with fixed obstacles and avoiding them, due to safe and secure routing, is the basic requirement of these systems. In this paper, the modified artificial potential field (APF) method is proposed for that robot avoids collision with fixed obstacles and reaches the target in an optimal path; using this algorithm, the robot can run to the target in optimal environments without any problems by avoiding obstacles, and also using this algorithm, unlike the APF algorithm, the robot does not get stuck in the local minimum. We are looking for an appropriate cost function, with restrictions that we have, and the goal is to avoid obstacles, achieve the target, and do not stop the robot in local minimum. The previous method, APF algorithm, has advantages, such as the use of a simple math model, which is easy to understand and implement. However, this algorithm has many drawbacks; the major drawback of this problem is at the local minimum and the inaccessibility of the target when the obstacles are in the vicinity of the target. Therefore, in order to obtain a better result and to improve the shortcomings of the APF algorithm, this algorithm needs to be improved. Here, the obstacle avoidance planning algorithm is proposed based on the improvement of the artificial potential field algorithm to solve this local minimum problem. In the end, simulation results are evaluated using MATLAB software. The simulation results show that the proposed method is superior to the existing solution.

/pdf/obstacle-avoidance-of-mobile-robots-using-modified-4pv81stwp3.pdf

Obstacle avoidance of mobile robots using modified artificial potential field algorithm

Grasping and assembly are essential tasks in high-precision robotic manipulation for industrial manufacturing as well as for home service applications. Many efforts have been devoted to this area in an attempt to meet the increasing precision requirement of the task. However, it remains a problematic objective to fulfill high precision, high reliability, high speed, and high flexibility all at once during one robotic manipulation task. To find answers to the above-mentioned problem, this article tries to categorize, review, and compare the recent works focusing on robotic grasping and assembly tasks to reveal some potential trends in this research area. The approaches will be divided into five groups based on the difference in the utilization of sensing or constraints. For each part, robotic grasping and assembly will be treated as practical cases to illustrate the concrete work in that area. This article could give the readers some knowledge on the current developments in robotic manipulation, and provide new thoughts on future direction in this area—inspiring new designs, structures, and systems to meet new requirements in applications in industrial manufacturing and home service.

A Survey of Methods and Strategies for High-Precision Robotic Grasping and Assembly Tasks—Some New Trends

In order to avoid dynamic obstacle timely during manufacturing tasks performed by manipulators, a novel method based on distance calculation and discrete detection is proposed. The nearest distances between the links of a manipulator and the convex hull of an arbitrarily-shaped dynamic obstacle obtained from Kinect-V2 camera in real-time are calculated by Gilbert–Johnson–Keerthi algorithm, and the minimum one is defined as the closest distance between the manipulator and the obstacle. When the closest distance is less than a safe value, whether the dynamic obstacle is located in the global path of the manipulator is determined by improved discrete collision detection, which can adjust detection step-size adaptively for accuracy and efficiency. If the obstacle will collide with the manipulator, set a local goal and re-plan a local path for the manipulator. The proposed method is implemented in Robot Operating System (ROS) using C++. The experiments indicate that the proposed method can perform safe and timely dynamic avoidance for redundant manipulators in human-robot interaction.

Dynamic obstacle avoidance for manipulators using distance calculation and discrete detection

BioTac is a humanoid finger sensor that can perceive multiple physical properties such as temperature, contact force, surface features, micro-vibration, etc. However measuring temperature with BioTac has a large delay due to its conducting medium, which is unfavorable for intelligent perception. So a method of temperature prediction based on Fourier's Law is proposed. Firstly, a multi-functional calibration device for BioTac is built. Secondly, the pressure signal of BioTac is calibrated for the next temperature calibration. Thirdly, the relational expression between the temperature signal from BioTac and the actual temperature is given using the Least Square method. Then the calculated temperature according to the relational expression is compensated by thermal flux, which is the predicted temperature. Finally, the proposed method is verified using the calibration device. The results show that the proposed method can greatly reduce the time of measuring temperature, and the prediction accuracy meets the demand of application.

Temperature prediction with humanoid finger sensor based on Fourier’s law

Planning path rapidly and optimally is one of the key technologies for industrial manipulators. A novel method based on Memory-Goal-Biasing–Rapidly-exploring Random Tree is proposed to solve high-d...

https://journals.sagepub.com/doi/pdf/10.1177/1729881418787049

Hong Nie

Papers

Dynamic obstacle avoidance for manipulators using distance calculation and discrete detection

Temperature prediction with humanoid finger sensor based on Fourier’s law

Optimal randomized path planning for redundant manipulators based on Memory-Goal-Biasing