Robot Working Research Articles

CARINA Project: Visual Perception Systems Applied for Autonomous Vehicles and Advanced Driver Assistance Systems (ADAS)

Autonomous mobile robots use computational techniques of great complexity so that to allow navigation in various types of dynamic environments, avoiding collisions with obstacles and always seeking to optimize the best route, ultimately enabling them to operate in a safe and precise manner. In order for navigation at this level to be possible, a variety of intelligent sensing techniques and computer vision are used. The potential of an intelligent computer vision system to detect and predict the actions of dynamic agents on the streets is applied to increase traffic safety with intelligent robotic vehicles. In this paper we present a systematic review of computer vision models for the detection and tracking of obstacles in traffic environments. Specifically, we will cover works involving 2D and 3D data fusion for both internal and external perception, as well as current trends regarding efficient model design and temporally-aware architectures. Alongside our review, we also provide a thorough discussion on the main positive and negative points of the state-of-the-art for detecting and tracking obstacles in Visual Robotic Attention works, as well as share our experience in applying visual perception for external obstacle detection and tracking, as well as internal (driver) monitoring. The results presented should serve as a compilation of the history of visual perception for autonomous mobile robots, and our contributions to the field, thus enabling an advance for research in the area of Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles.

Medical invention marketing strategies on buying: Surgical medical robot

The study aimed to identify the medical invention marketing strategies on buying (Surgical Medical Robot), the study used the descriptive approach to suit the purpose of the study. Sample of the study consisted of (100) participants divided (50) of marketing managers for the medical instrument companies and (50) medical employers related to working in surgery in the Jordanian hospitals. The study showed that the level of medical invention marketing strategies (Marketing Network, Design and Execution, Understanding Customer and the Promotion) and Buying Surgical Medical Robots in the Jordanian Hospitals were in the medium level. The study showed that the medical invention marketing strategies (Marketing Network, Design and Execution, Understanding Customer and the Promotion) have an impact on buying (Surgical Medical Robot) Jordanian hospitals. The study set of many recommendations as Work to raise awareness regarding medical robot surgery and Work by medical equipment companies to obtain the largest amount of information about the medical surgical robot, to increase the level of confidence of patients in this robot.

Digital model reconstruction through 3D Stereo Depth camera: a faster method exploiting robot poses

In industrial robotic contact-based operations it is necessary to have a detailed geometrical knowledge of the work-piece to automate the generation of the working trajectory. In many cases, the digital model is not available or it differs from its as built actual conditions. Vision sensors, especially 3D vision sensors allows to scan the work-piece and reconstruct its digital copy that is used for the generation of the robotic working trajectory. In this paper we compare two algorithms for the generation of the 3D model of an unknown work-piece based on the use of the RGB-D images taken from different perspectives. The first technique, based on standard image reconstruction methods commonly used for reconstruction of indoor scenes where error in the order of few centimeters is negligible, is exploited in this work in order to be exploited in contact-based robotic operations where the geometrical error has to be limited to few millimeters. It is based on the analysis of the images to estimate the camera pose taking each image. Based on the pose, the algorithm integrates then the information contained in the images in a unique volume representing the scene. The second algorithm directly uses the known poses of the robot, stored while capturing each image, to integrate the information to create the model. The two algorithms are compared to evaluate the accuracy, acquisition time and elaboration time. The analysis is done considering two kinds of objects, the first one with regular shape, the second one corresponding to an actual industrial object.

An Efficient Robot Precision Assembly Skill Learning Framework Based on Several Demonstrations

This paper proposes an efficient robot assembly skill learning framework based on only a few demonstrations. The assembly skill learning process consists of two phases, e.g., the pre-training phase and the self-learning phase. In pre-training phase, the assembly networks are initialized from demonstration data. A novel data augmentation model based on state transition model is designed, which only requires several human demonstrations to learn the parameters of the model and reduces the cost of demonstration data collection in pre-training. In self-learning phase, the pre-trained assembly networks are further optimized by a hybrid exploration strategy in assembly environment, which explores both parameter space and action space to increase exploration efficiency. On par with the learning framework, a fuzzy reward function balancing the efficiency and compliance of assembly is elaborately designed to evaluate action’s performance in assembly skill self-learning process. Series of physical experiments were well conducted on a sophisticated assembly platform to verify the effectiveness of the proposed efficient robot assembly skill learning framework. Experimental results demonstrate that the learning efficiency of the proposed framework is at least three times as efficient as the state-of-art methods, while the skill performance outperforms the state-of-art by more than 50%. Note to Practitioners—The motivation of this paper is to develop a skill learning framework to achieve efficient assembly skill learning for robot in real-world system. The proposed framework is only based on several demonstrations, which shows high practicability for robot skill learning. The self-learning method is dexterously used to optimize the learned assembly skill from demonstrations since the limited space of demonstrations. Besides, the hybrid exploration strategy and fuzzy reward strategy are well designed to improve the behavior of self-learning. The proposed framework can improve the efficiency and performance of robot assembly learning skill. It is extremely important for robot working in practical applications.

Analysis of Multi-Robot Patrolling Algorithms

This article is dedicated to analyzing the common problems of robots when patrolling indoors and the corresponding solution algorithms. In the article, four problems of patrol robots (whether centralized or non-centralized) during operation are listed: the overload of data to be processed when the robotic sensors are transmitting the data, the repetitiveness and simultaneity of the robot work, the incorrect execution of the algorithm and how to deal with the inevitable unknown external factors. The simultaneity of the robots is to be eliminated because robots need to explore independently in the patrol task. Subsequently, four algorithms and functionalities are introduced (Monte Carlo Tree Planning Algorithm, Rapid Exploring Random Tree Planning, Mutual Exclusion Algorithm, and Kalman Filter Algorithm). The question of how the four algorithms address the corresponding factors will be illustrated by an elaboration of the process by which the algorithms solve the problem.

Robotics: Social Robot

Abstract: Social robots are is also called to ‘family robot’ .In a social Robots are the study which provides to the communication about them selves . it is ourselves with people, and with the environment, within the joined to its role. This paper discusses the concept of a social robot. To the Current. Social robots also used in house and health care. Than the world’s first social robot designed by MIT robotics professor Cynthia Breazeal, the Jibo robot is often described as "the world's first family robot". Social Robots are helpful in health care and domestic areas, and in education and language learning’s, arts and entertainments. In this aim is to create guideline, an intended design for future developments of social robot. In this research paper the researcher has discussed about the introduction part of the social robots, applications of social robots a research has also focus on Benefits limitation and the future working of the social robots. In overall conceptual discussion of social robots the research has also focuses on future development

The Role of Robotics in the Development of the Economy of Russia and China

The post-industrial economy may have become possible as a result of the redistribution of labor resources in the sectoral limitation of GDP. As a result of the growth in labor productivity, which became possible due to the mechanization, accessibility and subsequent robotization of production processes, the world managed not only to make services as a priority in its economy, but to move to an innovative stage of development. Developed countries that took the risk to release part of their own labor resources from domestic production by replacing them with the work of robots, they now receive a huge amount of significant benefits from the development of robotics. Driven by the need to maximize them, they continue the processes of automating their national economy in an ideal situation — at the expense of robots of their own production, in extreme cases — at the expense of robots supplied from developed countries. Over the past century since the creation of the global robotics market, only countries with growing economies, primarily China, have managed to enter this market. This result was achieved thanks to a real assessment of the threats associated with an attempt to introduce robotics into the economy of a developing country, as well as serious advance work by the state aimed at leveling them. China's experience in entering the "world of robotics" can be borrowed by other developing countries, including Russia. It is important to understand that the success of the relevant reforms can only be achieved if two parallel processes are implemented: the robotization of production facilities already operating in the country and the organization of domestic production of robotics.

Numerical Investigation on ELF Electromagnetic Field Distribution of Pipeline Robot Tracking and Positioning System Using UAV

Pipeline robot, as a new type of equipment for pipeline operations such as pigging and detection, will play an increasingly important role in the operation and maintenance of oil and gas pipeline networks. The tracking and positioning technology during its operation process is one of the essential topics to improve the operating performance of pipeline robots and eliminate potential pipeline accidents. This paper presents the overall design of the wireless tracking and positioning system for pipeline robots based on extremely low frequency (ELF) electromagnetic method using the unmanned aerial vehicle (UAV). Starting from the classical electromagnetic theory, a mathematical model for the distribution of ELF electromagnetic field in buried metal pipeline environment is established. According to the characteristics of ELF electromagnetic wave transceiver and the model based on classical theory, the equivalent magnetic dipole transmission model is deduced. Based on the equivalent model, the attenuation characteristics of the ELF electromagnetic wave in the external space of the pipeline are analyzed by numerical simulation. The influence of the geometrical dimensions, environmental and working parameters, and other factors on the electromagnetic field intensity outside the pipeline is given at the same time. Finally, the distribution of ELF electromagnetic field in pipeline environment is discussed for horizontal-laying pipeline and inclined-laying pipeline, and the tracking method of pipeline robot is proposed on this basis. The proposed scheme is practical and effective, and it is suitable for real-time tracking and positioning of robot working in the pipelines whose slope is no more than 60 degrees with known or unknown distribution.

Dubin’s Curve of RRT* Merged With A*

One of the fundamental problems in mobile robotics is a robot path planning of the mobile robot through its environment. Path planning problem for the mobile robot with differential constraints using modified RRT (Rapidly exploring random tree) algorithm based on Dubin’s curves. the planning problem is considered as a problem of finding a feasible path between the initial and goal point in a static environment with obstacles. This process can be conducted either using local information from sensors or by emloying global a-priori known information about robot’s environment. The problem is how to generate a path from the beginning to the destination point gradually during movement using modified RRT (Rapidly exploring random tree) algorithm based on Dubin’s curves. Combining the dubin curve RRT* algorithm with A* is a new method that can calculate the entire path from the starting point of the destination before moving using global information about the map. The purpose of making the path is to make it easier for the operator to determine the path that must be traversed by the robot. The way the robot works is to read the line made by the operator using matlab based on the map, then matlab will calculate the distance of the path to be traversed using an algorithm from the star point to the goal point. Based on the simulation results that have been carried out this method is more efficient when compared to the RRT* or A* algorithms. because this algorithm can produce a path with the shortest path with a fast time to get to the destination point without crashing into obstacles. By adding a new algorithm to find a new path optimally to get a path that is close to optimal by combining and adjusting several feasible paths and also adding a searching-based algorithm, namely A* combined with Dubin Curve- RRT* is sampling based, where the A* algorithm has a function heuristic used to increase the cost and time of searching.

Digital twin design and analytics for scaling up electric vehicle battery production using robots

As electric vehicle adoption accelerates and demand increases, the inability to produce batteries in sufficient quantities has emerged as a critical bottleneck in the electric vehicle supply chain. Given the impending climate change crisis, resolving this bottleneck is imperative to accelerate the transition to a zero-emission electric mobility future. One potential solution is the use of robotics for fast and cost-effective assembly of batteries at scale. This study proposes a three-stage digital twin design and analysis method to develop robotic workcells for fast and cost-effective assembly of electric vehicle battery modules. Using digital twin design and simulation, robotic assembly line configurations have been developed for battery module production at different scales. Digital twin analytics was used to evaluate and optimise the proposed robotic battery assembly system for speed and cost. Industrial automation experts were consulted to further improve robotic work cell layouts to minimise investment in robots. Because digital twins of robotic workcells have been used, the configurations of the battery assembly line, as designed and validated, are ready for immediate implementation. For practitioners, this study offers heuristic methods to determine the appropriate assembly line configuration, the required number of robots and humans, for a desired production volume. For researchers, this study outlines promising areas for future investigation.

Hand Gesture Controlled Robot

The work consists of the working model of hand Gesture controlled robot. A robot is the approach which deals with construction, design and operation. This procedure acts as a medium between the human and the robot through physical change such as tilting of the hand. This approach is related to robot and their design, manufacture, flexibility, redundancy, fault tolerance and some other researchers are on completely automating a manufacturing process or a task, by providing sensor based to the robot arm. As the whole world is now moving on to make the repeated tasks that were made by humans for all these years through robots. To save human efforts the automation is playing an important role in the system. This approach is used for regular and frequently carried work. This device can be very useful for surveillance, military operations and industrial grade robotic arms physically challenged people. The way a hand gesture-controlled robot works is with the help of a sensor module called as accelerometer, which detects the motion made by the user hand and act accordingly. The design and implementation of a gesture-controlled robot using MPU6050 sensor is proposed. The controller is made to imitate the human hand movements using a hand glove which is attached to the accelerometer that is mounted on it. Keyw

Layout optimization of robot forging unit based on genetic algorithm

To improve the productivity of automated forging production units, reasonable layout is very important. In this paper, the layout optimization method of the robot working unit was studied to improve the production efficiency of forged crankshaft products, the bottleneck production unit is taken as the research object to find a satisfactory solution to the layout planning. Based on a mathematical model, a hierarchical description method of robot workspace and a prediction method of transition points were proposed. The robot running time and operability were used as evaluation indexes of the layout. The NSGA-II algorithm was used to optimize the layout scheme to obtain a better solution, and the optimized solution has better operability and runtime performance. The simulation results of professional software showed that the proposed layout optimization method and layout scheme were reasonable and significantly improved.

Parallel Manufacturing for Industrial Metaverses: A New Paradigm in Smart Manufacturing

Briefing: To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operations of those systems, where Cyber-Physical-Social Systems (CPSSs) and the Internet of Minds (IoM) are regarded as its infrastructures and the “Artificial systems”, “Computational experiments” and “Parallel execution” (ACP) method is its methodological foundation for parallel evolution, closed-loop feedback, and collaborative optimization. In parallel manufacturing, social demands are analyzed and extracted from social intelligence for product R&D and production planning, and digital workers and robotic workers perform the majority of the physical and mental work instead of human workers, contributing to the realization of low-cost, high-efficiency and zero-inventory manufacturing. A variety of advanced technologies such as Knowledge Automation (KA), blockchain, crowdsourcing and Decentralized Autonomous Organizations (DAOs) provide powerful support for the construction of parallel manufacturing, which holds the promise of breaking the constraints of resource and capacity, and the limitations of time and space. Finally, the effectiveness of parallel manufacturing is verified by taking the workflow of customized shoes as a case, especially the unmanned production line named FlexVega.

Advantages of preoperative counseling with video for robotic rectal cancer surgery compared with conventional counseling: A randomized controlled trial.

Surgeons should provide patients with appropriate explanations before surgery and obtain informed consent. However, this process requires time and effort and can be a great burden. The purpose of this study was to compare preoperative counseling with video (VC) and conventional counseling (CC) for rectal cancer patients. Rectal cancer patients indicated for surgery were included between April 2021 and March 2022, and eligible patients were randomly assigned to the CC and VC groups. The primary outcomes were the comprehension, satisfaction, and anxiety levels, and the secondary outcome was the preoperative counseling time. This exploratory study protocol was registered with the UMIN Clinical Trials Registry (UMIN000038133). We included 13 patients in the CC group and 17 in the VC group. All eligible patients were scheduled for robotic rectal cancer surgery. There were no significant differences between the two groups, including patients' general condition, preoperative diagnosis, and planned procedures. Although the comprehension, satisfaction, and anxiety test scores were not significantly different between the groups, the preoperative counseling time was significantly shorter in the VC group than in the CC group (20 vs. 35 minutes, P=.002). A 4-year college degree significantly increased the counseling time, whereas VC significantly decreased it. Using videos in preoperative counseling for rectal cancer patients is useful. This novel method could reduce the burden on surgeons during preoperative counseling in the era of robotic surgery and work style reforms.

The human-following strategy for mobile robots in mixed environments

The robot behavior strategy is considered as a crucial part in the human-following task to help the robot maintain an appropriate distance and orientation to the selected target person (STP) with a smooth and safe manner. As usual, the robot is uniquely considered to follow the STP in a specific class of environments, such as unknown environments (non-mapped environments) or known environments (mapped environments). However, in real-life applications, the robot is sometimes requested to follow the STP in various types of environments, both in known and unknown ones. This observation raises the need to propose an alternative method to challenge the mentioned issue, as well as to break the current limit of the human-following function. In this paper, a new approach for the human-following strategy is proposed in which the mobile robot is enabled to follow the STP in mixed environments (non-mapped and mapped). In non-mapped environments, only the STP and the obstacle information with respect to the robot local coordinates are considered, whose purpose is to make the robot work without any prior understandings about its working environment. However, after the robot entered mapped environments, its prior knowledge of the working environment is leveraged to fulfill some additional requirements during the cooperation, such as the mobile robot in factories is not allowed to enter some specific areas even when the STP is executing technical tasks inside. Additionally, in this paper, a human-like inference mechanism is also introduced for the human-following strategy by using an extended hedge algebras. The proposed method is experimentally verified both in factories and laboratories.Demo Video Link: https://www.youtube.com/watch?v=YGrWU6ldKuwSince real videos in the factory are not allowed to publish, only visualization (in Rviz) is presented for demos in such kinds of environments. The visualization is synchronous with the real executions of the human–robot interactions. The robot used in the factory is an autonomous mobile robot (dimension 0.5 (m) ×1.0 (m), weight 120 (kg), carrying a tool cabinet around 300(kg))). The mobile robot is following the worker to support them during the technical processes in the car production line. In the video, the robot is represented by a green rectangular, and the STP is represented by a cylinder (with a sphere on its head) The events in the demo video are described more clearly inAppendix A.

Enabling automated facility maintenance from articulated robot Collision-Free designs

Key challenges found in some facilities maintenance (FM) operations include the dependency on placing sophisticated workers in undesirable working conditions that could make them susceptible to accidents. Robot-assisted in-situ facilities maintenance represents new opportunities by assisting human operators when exposed to harsh environments. However, given the complexities and potential varieties of advanced robotic machinery available for use in facility maintenance workplaces in the future, there is still a legitimate risk of collisions between future robotic systems and the facility structure during the robot-assisted processes. This paper proposes and tests a simulation-based collision-free design method for future facilities that may be benefited from a robot-assisted FM process. At the most fundamental level, we consider interactions between the articulated manipulator (robot) and the surrounding facility structure. Inverse Kinematics (IK) and game engines are used to simulate the possible collisions between a given robot and the parameterized facility layout. To account for the uncertainty about the kinematic specifications of the future robotic machinery, a Monte Carlo method is used to model unique priority circumstances for each joint on the articulated manipulator. The simulation result, presented as the robot work zone envelope, is then used to estimate the collision probability given a certain design parameter, and the corresponding optimal design that balances the initial construction cost and the FM costs. The method is assessed for identifying a 3D spatial collision probability cloud within reach of a 7 DOF articulated manipulator that is marginally positioned within a pressure valve piping facility. These insights can provide future facility designers, managers, and equipment operators with a quick and flexible 3D spatial collision probability indicator to better design the facility and proximity limitations of any articulated manipulator positioned throughout a confined space for future robot-assisted FM processes.

Wire Harness Assembly Process Supported by a Collaborative Robot: A Case Study Focus on Ergonomics

Products and assets are becoming increasingly “smart”, e.g., mechatronic, electronic, or cyber-physical. In the lack of fully reliable wireless solutions, extensive wiring and wire bundling into wire harnesses are needed. This has manufacturing implications, leading to increasingly complex wire harness assembly processes, where numerous components, connectors, and cables are assembled, connecting critical and non-critical electric and electronic systems in smart products and assets. Thus, wire harnesses demand is rapidly rising in most industries, requiring human or robotic work. Often, required work tasks are repetitive and physically demanding, while still needing people for quality reasons. An attractive solution would therefore be humans collaborating with robots. Unfortunately, there are very few scientific studies on automation solutions using collaborative robots (cobots) for wire harness assembly process tasks to increase process productivity and improve work ergonomics. Furthermore, wire harness assembly process tasks are presently carried out 90% manually in this industry, causing serious ergonomic problems for assembly workers who perform such tasks daily. The challenge is reducing the ergonomic risks currently present in many established wire harness assembly processes while improving production time and quality. This paper presents an early prototype and simulation to integrate a cobot into a wire harness assembly process, primarily for work ergonomic improvements. The use of a cobot is specifically proposed to reduce ergonomic risks for wire harness assembly workers. Two methodologies: RULA and JSI were used to evaluate the ergonomics of the task of cable tie collocation. The real-world case study results illustrate the validation of a cobot which significantly reduced non-ergonomic postures in the task of placing cable ties in the wire harnesses assembly process studied. An ergonomic analysis without the cobot (the actual process) was conducted, based on RULA and JSI methodologies, presenting the highest possible scores in both evaluations, which calls for urgent changes in the current wire harness assembly process task studied. Then, the same analysis was performed with the cobot, obtaining significant reductions in the ergonomic risks of the task at hand to acceptable values.

Behavior Analysis for Increasing the Efficiency of Human–Robot Collaboration

In this study, we proposed a behavior analysis for increasing the efficiency of human–robot collaboration in an assembly task. This study was inspired by previous research, in which a set of operator intentions in assembly was translated into an intention graph to formulate a probabilistic decision model for planning robot actions in the presence of operator intention ambiguity and perception uncertainty. Here, we achieved improvement by considering the analysis of human behavior in the form of fatigue and adaptation ability. We also switched the collaboration scheme from cooperative to collaborative, in which both the robot and operator work in parallel, not sequentially. We then tested the proposed method with chair assembly and the results indicated that shortening the assembly duration increased the effectiveness of the assembly process. The results also indicated that the proposed method for assembling 50 chairs was 4.68 s faster than the previous method.

Communication-Focused Top-Down Design of Robotic Systems Based on Binary Decomposition

This article proposes a formal method of designing robotic systems focusing on communication between components, as well as standardization of the messages between those components. The objective is to design a robotic system controller in a systematic way, focusing on communication at an abstract agent level. Communication, thus organized, and its properly defined specification facilitate the system’s further development. The method uses a standard message structure, based on IEEE FIPA standards, for communication within robotic systems composed of agents. Communication-focused top-down design of robotic systems based on binary decomposition is proposed, and used to design a companion robot working in the kitchen environment. The implemented robotic system is verified based on whether or not the specification conforms to the specified requirements. The characteristics of the designed communication are evaluated. The obtained results prove that the proposed method of designing robotic systems is formally correct, it facilitates the implementation of agents, and separates specification of the system from its implementation. The method of designing robotic systems is correct and useful. The proposed formal notation facilitates understanding of how the system operates and organizes the design process. It puts the communication between system components at the forefront. The resulting system specification facilitates the implementation. The tools for experimental evaluation of its characteristics enable the confirmation that it fulfills the requirements, and that the communication between the system components is correct.

Design of UVC Surface Disinfection Robot with Coverage Path Planning Using Map-Based Approach At-The-Edge

In response to the issue of virus contamination in the cold-chain warehouse or hospital environment under the influence of the COVID-19, we propose the design work of a disinfection robot based on the UVC radiation mechanism using the low-computational path optimization at-the-edge. To build a surface disinfection robot with less computing power to generate a collision-free path with shorter total distance in studies, a 2D map is used as a graph-based approach to automatically generate a closed-loop disinfection path to cover all the accessible surfaces. The discrete disinfection points from the map are extracted with effective disinfection distances and sorted by a nearest-neighbor (NN) search over historical trajectory data and improved A * algorithm to obtain an efficient coverage path to all accessible boundaries of the entire area. The purpose of improved A * algorithm with NN is not to find the optimal path solution but to optimize one with reasonable computing power. The proposed algorithm enhances the path-finding efficiency by a dynamically weighted heuristic function and reduces the path turning angles, which improves the path smoothness significantly requiring less computing power. The Gazebo simulation is conducted, and the prototype disinfection robot has been built and tested in a real lab environment. Compared with the classic A * algorithm, the improved A * algorithm with NN has improved the path-finding efficiency and reduced the path length while covering the same area. Both the simulation and experimental results show that this approach can provide the design to balance the tradeoffs among the path-finding efficiency, smoothness, disinfection coverage, and computation resources.