Robot Working Research Articles

Online Topological Mapping on a Quadcopter with Fast Growing Neural Gas

This paper presents an online topological mapping method on a quadcopter with fast-growing neural gas. Recently, perceiving the real world in 3D space has become increasingly important, and robotics is no exception. Quadcopters are the most common type of robot working in 3D space. The ability to perceive 3D space is even required in order to enable real-time autonomous control. Dense maps are simply unpractical, while sparse maps are not suitable due to a lack of appropriate information. Topological maps then offer a balance between computational cost and accuracy. One of the most well-known unsupervised learning methods for topological mapping is growing neural gas (GNG). Unfortunately, it is difficult to increase the learning speed due to the traditional iterative method. Consequently, we propose a new method for topological mapping, called simplified multi-scale batch-learning GNG, by applying a mini-batch strategy in the learning process. The proposed method has been implemented on a quadcopter for indoor mapping applications. In addition, the topological maps are also combined with the tracking data of the quadcopter to generate a new global map. The combination is simple yet robust, based on rotation and translation strategies. Thus, the quadcopter is able to run the algorithms in real-time and maintain its performance above 30 fps.

A high-response-frequency bimodal network polyacrylate elastomer with ultrahigh power density under low electric field

Dielectric elastomers, used as driver modules, require high power density to enable fast movement and efficient work of soft robots. Polyacrylate elastomers usually suffer from low power density under low electric fields due to limited response frequency. Here, we propose a bimodal network polyacrylate dielectric elastomer which breaks the intrinsic coupling relationship between dielectric and mechanical properties, featuring relatively high dielectric constant, low Young’s modulus, and wide driving frequency bandwidth (~200 Hz) like silicones. Therefore, an ultrahigh power density (154 W kg−1@20 MV m−1, 200 Hz) is realized at low electric field and high resonance frequency, 75 times greater than at 10 Hz. Further, a rotary motor is developed, reaching an impressive speed of 1245 rpm at 19.6 MV m−1 and 125 Hz, surpassing previous acrylate-based motors and entering the high-speed domain of silicone-based motors. These findings offer a versatile strategy to fabricate high-power-density dielectric elastomers for low-electric-field soft actuators.

Robots that Can Survive the Egg Drop

If you ever did the egg drop challenge, you know it is hard to build something that can protect a fragile egg from crashing into the ground and breaking. Engineers are building soft robots called tensegrity robots, which are designed to survive harsh crashes. The word tensegrity comes from “tension” and “integrity”. It means the robot is made of stiff bars held together with stretchy cables. This flexible structure helps a tensegrity robot absorb the impact from crashes. Someday, these robots might be used to explore dangerous places like deep caves or other planets. These robots could fall off cliffs or into craters. Right now, engineers are making tensegrity robots better and easier to control. In this article, we will explain how tensegrity robots work. We will discuss their advantages, their disadvantages, and what they can be used for.

Fault detection of RV reducer cycloidal gear under robot working conditions based on optimization improved envelope spectrum sideband energy ratio

Abstract Under industrial robot operating conditions, the cycloidal gear in the rotary vector(RV) reducer in the robot joint runs in a compound rotation motion with a low-speed and incomplete cycle, which complicates the fault detection for the cycloidal gear. Until now, no effective detection method for the cycloidal gear tooth fault under industrial robot operating conditions has been reported. Consequently, a method based on optimization improved envelope spectrum sideband energy ratio is proposed in this paper. Firstly, encoder signals are acquired and used to estimate the instantaneous angular speed (IAS) signals, which are then separated into two sets of data based on rotational directions. Then, the data corresponding to the approximately stable speed is truncated and connected to form a constructed signal. Next, the coherence of the constructed signal is calculated using the fast spectral coherence algorithm. Subsequently, the improved envelope spectrum sideband energy ratio is used as the objective value, and a global optimization algorithm is employed to determine the integration frequency band of the improved envelope spectrum (IES). Finally, the IES of this frequency band is calculated to obtain the fault-relatedorder characteristics. An RV reducer test rig was used for the experiment, and the analysis results from the proposed approach, cyclic spectral coherence (CSCoh), and improved envelope spectrum via feature optimization-gram (IESFOgram) were contrasted. Experiment results show that the proposed method is valid for the detection of tooth faults in the cycloidal gear of the RV reducer in robot operating conditions.

MICROCONTROLLER MANAGEMENT SYSTEM OF MANIPULATOR MANAGE

Currently, most manipulators are driven by a DC or AC motor. The encoder is used as a speed positioning and feedback device in the manipulator control system.The spectrum of available solutions in the field of microcontroller control systems of manipulators is considered in the article. The circuit of the controller board has been developed to control the transfer of the manipulator manga.The analysis of the element base included in the composition of the control board has been performed. The manipulators used for the automation of biochemical analysis allow to improve the quality of the conducted analysis and the repeatability of the robot's work. Also, due to continuous performance of the work, it creates conditions to increase productivity as a whole. Keywords: manipulation, robot, microcontroller, manipulator, transmission.

Study of Collaborative Space in Rebar Tying Robotic Systems

Abstract In the process of rebar tying operations conducted by multiple robots, the flexibility and operability of the robot’s end effector directly influence the overall performance of the rebar tying system. This reflects the crucial role of the coordinated working capability of multiple robots in the trajectory planning of the rebar tying system. Utilizing an eight degrees of freedom rebar tying system composed of two collaborative robots and a truss structure, the D-H (Denavit-Hartenberg) dynamic model for each robotic arm is established. The working area of the system is ascertained via Monte Carlo methods. Flexibility and operability are adopted as metrics to evaluate the system’s performance, subsequently leading to the formulation of a mathematical model for assessing the system’s flexibility. MATLAB is employed to delineate the robotic working range and simulate analysis of flexibility and operability when operating on the rebar tying plane, yielding an intuitive distribution of system flexibility. By analysing the distribution of flexibility and operability across the working plane at varying robot spacing intervals, an optimal robot movement distance can be determined. This ensures that during operational tasks, the rebar tying system not only possesses a larger total working area but also maintains a high level of flexibility and operability within the collaborative region, thereby fulfilling the objective of enhancing workspace utilization and improving rebar tying efficiency.

Robot Joint Cycloidal Gear Tooth Fault Detection in Robot Working Conditions Based on Piecewise Mean Difference

Robot Joint Cycloidal Gear Tooth Fault Detection in Robot Working Conditions Based on Piecewise Mean Difference

Multi-robot collision avoidance method in sweet potato fields.

Currently, precise spraying of sweet potatoes is mainly accomplished through semi-mechanized or single spraying robots, which results in low operating efficiency. Moreover, it is time-consuming and labor-intensive, and the pests and diseases cannot be eliminated in time. Based on multi robot navigation technology, multiple robots can work simultaneously, improving work efficiency. One of the main challenges faced by multi robot navigation technology is to develop a safe and robust collision avoidance strategy, so that each robot can safely and efficiently navigate from its starting position to the expected target. In this article, we propose a low-cost multi-robot collision avoidance method to solve the problem that multiple robots are prone to collision when working in field at the same time. This method has achieved good results in simulation. In particular, our collision avoidance method predicts the possibility of collision based on the robot's position and environmental information, and changes the robot's path in advance, instead of waiting for the robot to make a collision avoidance decision when it is closer. Finally, we demonstrate that a multi-robot collision avoidance approach provides an excellent solution for safe and effective autonomous navigation of a single robot working in complex sweet potato fields. Our collision avoidance method allows the robot to move forward effectively in the field without getting stuck. More importantly, this method does not require expensive hardware and computing power, nor does it require tedious parameter tuning.

The impact of robotic working patterns on employee work life and job satisfaction: evidence from ethnic minority businesses in the UK

The impact of robotic working patterns on employee work life and job satisfaction: evidence from ethnic minority businesses in the UK

Robotical Automation in CNC Machine Tools: A Review

Abstract Robotics and automation have significantly transformed Computer Numerical Control (CNC) machining operations, enhancing productivity, precision, and efficiency. Robots are employed to load and unload raw materials, workpieces, and finished parts onto CNC machines. They can efficiently handle heavy and bulky components, reducing the demand of manual labour and minimizing the risk of injuries. Robots can also be used in CNC machine tools to perform tasks such as automatic tool changing system, part inspection, and workpiece positioning. Automation technologies, including in-line inspection systems and Non-Destructive Testing (NDT) methods, can be integrated into CNC machining cells to enhance accuracy and reduce scrap and rework in machining operations. These systems collect real-time data on process parameters and machine tool performance to predict maintenance, optimize machining parameters, and improve overall efficiency. In the current study, applications of robotics and automation in the modification of CNC machine tools are reviewed and discussed. Different applications of robotics and automation in CNC machine tools, such as automated material handling, automatic tool changing, robotic work cells, adaptive machining, machine tending, quality inspection, data monitoring and analysis, and production line integration, are discussed. Thus, by analysing recent achievements in published papers, new ideas and concepts of future research works are suggested. As a result, accuracy as well as productivity in the process of part production can be enhanced by applying robotics and automation in CNC machining operations.

Public's Perception and Knowledge of Using Robotics in General Surgery in Eastern Region, Saudi Arabia.

Robotics in general surgery is a field that involves the use of robotic systems to assist surgeons in performing various types of surgical procedures. The objective of this study was to evaluate the perception and knowledge of robotic surgery among the Eastern Region's population. This cross-sectional study used an electronic questionnaire that was developed using Google Docs. It included males and females aged above 18 years who lived in the Eastern Province. Participants who were below 18 or above 65 years of age, or non-Saudi, or people who lived in other than the Eastern Region of Saudi Arabia were excluded from the study. A total of 500 responses were received via the Google Form, and 81 subjects of them were excluded from the study. Approximately half of the participants were aware of the existence of general robotic surgery, while the other half had no prior knowledge about it. When assessing the participants' understanding of how robotic surgery works, a significant proportion provided incorrect responses. In terms of the advantages of general robotic surgery, the most commonly recognized benefit was that it makes the doctor's life easier, followed by more accurate surgical results. However, the participants' understanding of the disadvantages of robotic surgery was not as accurate. A substantial portion of participants were unsure about the disadvantages. The general public of the Eastern Region in Saudi Arabia showed a derated level of knowledge about the use of robotics in general surgery. Furthermore, a major portion of people were unaware of the availability of robotic surgery in Saudi Arabia. Educational programs are warranted to facilitate the implantation of robotic surgery in Saudi Arabia.

PHANTOM CHAINS TONTOR OF BIONIC OBJECT'S MOVEMENTS OF AUTOMATED SYSTEMS. Part 1

This presented work results provides an understanding of how phantom life cycle diagrams of abstract objects can be formed based on the conditions of their existence. Thus, an essential feature of the action of these objects is their possibility of application in automated systems, which is an important aspect of the development of technical bionic means and systems. The problem of using a phantom for modeling actions, movements of objects in space, features of the obtained results is quite widely used in various fields of scientific research. However, there remain tasks related to understanding how the main actions of robotic working bodies of automated systems take place. Thus, it becomes possible to create formalized models of the processes of performing actions of experimental objects in medicine, industry, astronomy, based on phantom constituents of chain and step geometric elements. Thus, it is possible to present similar bionic objects in medical automated systems, which refers to the design of bionic prostheses, exoskeleton systems, as well as systems for scientific research of biomechanical properties of objects. At the same time, we analyze the peculiarities of motor movements, for which we create and analyze phantom models of TONTOR steps and their combination into phantom chains. Prospects for further research, which will be presented in the next part of this work, are the creation of analytical models of phantom features of the existence of various bionic technical means in view of their connection between the volume of the abstract object and the phantom. Similar analytical approaches make it possible to determine the phantom matrix model of the life cycle of a bionic abstract object in automated systems.

A new novel recognition and positioning system of black light-absorbing volute for automation depalletizing development

Abstract In the application of vision measurement, the black light-absorbing object is difficult to reflect the structured light from infrared emitter of the RGB-D camera. Therefore, an image recognition algorithm based on reference environment information is proposed to acquire the spatial positioning information of black volutes in the depalletizing system. The hardware system of the depalletizing system is mainly constructed of an upper computer, a six-axis industrial robot, an RGB-D camera and an end adsorption device. Firstly, the horizontal position information of each volute placed on the cardboard is obtained by the depth differences between the cardboard and the volute. Then, the depth information of the volute is obtained by the upper cardboard depth through collecting the position of the end vacuum suction cup triggered by feedback signal from vacuum generator. Secondly, a regional planar hand-eye calibration method is developed to improve the calibration accuracy in two-dimensional coordinates. The regional calibration method divides the robot working area into four regions: upper left, lower left, upper right, and lower right. The transformation matrix of each region is calculated separately. Finally, the depalletizing experiment is conducted on the three types of volutes. It is concluded that the average positioning error of the grasping center point of each volute obtained by our method is 3.795 mm, and its standard deviation is 1.769 mm. The average value of regional planar hand-eye calibration error is 4.044 mm, and its standard deviation is 1.501 mm. Under a stack of materials with dimensions of 1350 mm × 1350 mm × 1500 mm, the maximum error is controlled within 15 mm. Additionally, when combined with the end feedback compensation mechanism, the success rate for grasping all three volutes reaches 100%.

What did you hear and what did you see? Understanding the transparency of facial recognition and speech recognition systems during human–robot interaction

As social robots begin to assume various social roles in society, the demand for understanding how social robots work and communicate grows rapidly. While literature on explainable artificial intelligence suggests that transparency about a social robot’s working mechanism can evoke users’ positive attitudes, transparency may also have negative outcomes. This study investigates the paradoxical effects of the transparency of facial recognition technology and speech recognition technology in human–robot interactions. Based on a lab experiment and combined analyses of users’ quantitative and qualitative responses, this study suggests that the transparency of facial recognition technology in human–robot interaction increases users’ social presence, reduces privacy concerns, and enhances users’ acceptance of robots. However, exposure to both facial and speech recognition technologies revives users’ privacy worries. This study further parses users’ open-ended evaluation of the prospective application of social robots’ tracking technologies and discusses the theoretical, practical, and ethical value of the findings.

Genesis of economic integration of Ukraine into the EU

The paper examines the genesis of economic integration of Ukraine to the EU. The purpose of the paper is to investigate the genesis of economic integration of Ukraine to the EU and develop recommendations for their development. The result of bilateral trade integration following the implementation of the consolidated and all-inclusive free trade zone was the modernization of Ukraine's trade policy. The primary dominants may include: the increase in trade turnover between the countries and the increase in the share of European countries in the structure of foreign trade of Ukraine; changes in import duties; improved access to the market; harmonization of legislation; establishment of tariff quotas; а further reduction in non-tariff barriers to trade; home ownership of the region is one hundred percent improved robotic work; harmonization of the technical regulation system; systems of standardization, metrology, conformity assessment and market visibility; sanitary and phytosanitary visits; Strengthening the protection of intellectual rights. The genesis of economic integration of Ukraine to the EU was investigated. An analysis of the Vikonanny Ugodi about association for 2022 and 2023 was carried out. We have analyzed the strengths and weaknesses, the emerging opportunities and threats to the integration of Ukraine into the EU. Directly from further scientific research, it is important to look at the most important aspects of the economic integration of Ukraine, since the most important payments will ensure the formation of the revenue side of the budget from further It is re-divided into different socio-economic goals of the state.

Model-free visual servoing based on active disturbance rejection control and adaptive estimator for robotic manipulation without calibration

PurposeVisual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment.Design/methodology/approachThis paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model.FindingsThe various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks.Originality/valueCompared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.

The Design and Development of Delta Arm for Multi-Purpose Agribots

Many challenges and obstacles prevail in the agricultural fields, such as weed removal, horticulture, and spraying herbicides and fertilizers. Individual robots for all these tasks cost a lot, which ordinary farmers cannot afford. The delta arm has to perform versatile functions like spraying and weed removal with great accuracy and reduced environmental impact. The primary objective of this research is to design a delta arm that can move in all directions efficiently. The driving and driven arm in the delta arm design should be correlated, which helps with the proper positioning of the end effector carrier. Similarly, the moving platform and the fixed platform are designed in a circular form. These measurements give a proper design and make the robotic arm work properly as it can move in all three degrees of freedom in XYZ directions. The NVIDIA jetson orin nano operates as the controlling unit of the delta arm. The study proved that the delta arm had achieved an accuracy rate of 98% at a speed of 107.5 mm/s, making it well-suited for agricultural field operations. In addition, the delta arm exhibits the capability to handle an end effector weighing up to 300 g. Therefore, introducing the delta arm agribot in the row-based agricultural field can make a revolution in the upcoming years as it can perform versatile tasks at a high speed.

Nighttime Harvesting of OrBot (Orchard RoBot)

The Robotics Vision Lab of Northwest Nazarene University has developed the Orchard Robot (OrBot), which was designed for harvesting fruits. OrBot is composed of a machine vision system to locate fruits on the tree, a robotic manipulator to approach the target fruit, and a gripper to remove the target fruit. Field trials conducted at commercial orchards for apples and peaches during the harvesting season of 2021 yielded a harvesting success rate of about 85% and had an average harvesting cycle time of 12 s. Building upon this success, the goal of this study is to evaluate the performance of OrBot during nighttime harvesting. The idea is to have OrBot harvest at night, and then human pickers continue the harvesting operation during the day. This human and robot collaboration will leverage the labor shortage issue with a relatively slower robot working at night. The specific objectives are to determine the artificial lighting parameters suitable for nighttime harvesting and to evaluate the harvesting viability of OrBot during the night. LED lighting was selected as the source for artificial illumination with a color temperature of 5600 K and 10% intensity. This combination resulted in images with the lowest noise. OrBot was tested in a commercial orchard using twenty Pink Lady apple trees. Results showed an increased success rate during the night, with OrBot gaining 94% compared to 88% during the daytime operations.

Framing the predictive mind: why we should think again about Dreyfus

AbstractIn this paper I return to Hubert Dreyfus’ old but influential critique of artificial intelligence, redirecting it towards contemporary predictive processing models of the mind (PP). I focus on Dreyfus’ arguments about the “frame problem” for artificial cognitive systems, and his contrasting account of embodied human skills and expertise. The frame problem presents as a prima facie problem for practical work in AI and robotics, but also for computational views of the mind in general, including for PP. Indeed, some of the issues it presents seem more acute for PP, insofar as it seeks to unify all cognition and intelligence, and aims to do so without admitting any cognitive processes or mechanisms outside of the scope of the theory. I contend, however, that there is an unresolved problem for PP concerning whether it can both explain all cognition and intelligent behavior as minimizing prediction error with just the core formal elements of the PP toolbox, and also adequately comprehend (or explain away) some of the apparent cognitive differences between biological and prediction-based artificial intelligence, notably in regard to establishing relevance and flexible context-switching, precisely the features of interest to Dreyfus’ work on embodied indexicality, habits/skills, and abductive inference. I address several influential philosophical versions of PP, including the work of Jakob Hohwy and Andy Clark, as well as more enactive-oriented interpretations of active inference coming from a broadly Fristonian perspective.

Path planning for robot search task using belief criteria decision-making

PurposeThis study aims to realize efficient, fast and safe robot search task, the belief criteria decision-making approach is proposed to solve the object search task with an uncertain location.Design/methodology/approachThe study formulates the robot search task as a partially observable Markov decision process, uses the semantic information to evaluate the belief state and designs the belief criteria decision-making approach. A cost function considering a trade-off among belief state, path length and movement effort is modelled to select the next best location in path planning.FindingsThe semantic information is successfully modelled and propagated, which can represent the belief of finding object. The belief criteria decision-making (BCDM) approach is evaluated in both Gazebo simulation platform and physical experiments. Compared to greedy, uniform and random methods, the performance index of path length and execution time is superior by BCDM approach.Originality/valueThe prior knowledge of robot working environment, especially semantic information, can be used for path planning to achieve efficient task execution in path length and execution time. The modelling and updating of environment information can lead a promising research topic to realize a more intelligent decision-making method for object search task.