Cooperative Robots Research Articles

Wireless Distributed Consensus for Connected Autonomous Systems

Connected critical autonomous systems (C-CAS) are envisioned to significantly change our life and work styles through emerging vertical applications such as autonomous vehicles and cooperative robots. However, as the scale of the connected nodes continues to grow, their heterogeneity and cyber-security threats are more eminent, and conventional centralized communications and decision-making methodology are reaching their limit. This paper is the first exploration of a trustworthy and fault-tolerant framework for C-CAS for achieving hyper-reliable global decision-making in a trustless environment, where the connected sensors/nodes are less reliable due to either communication failure or local decision error (e.g., by sensing algorithm/AI, etc.). The proposed framework is based on two iconic distributed consensus (DC) mechanisms, practical Byzantine fault tolerance (PBFT) and Raft, under the proposed PICA (Perception-Initiative-Consensus-Action) protocol with wireless connections among the nodes. We first analytically derived consensus reliability in six different system models. The other fundamental performance metrics such as the consensus throughput and latency, node scalability and reliability gain are also analytically derived. These analytical results provide basic design guidelines for wireless Distributed Consensus (WDC) usage in the C-CAS systems. The results show that WDC significantly improves overall system reliability with the increasing number of participating nodes.

Structure Cursor Fixing and Splicing Based on Cooperative Robot

In the field of machine vision, surface structured light image stitching can generate high-resolution images with large field of view, which can meet the needs of enterprise production. This paper introduces a 3D image Mosaic method based on robot arm and fringe projection technology. In this method, a surface structured light vision sensor installed at the end of the manipulator is used to scan and reconstruct the workpiece surface. The sensor consists of a DLP projector and a 3D camera. A set of sinusoidal structured light is projected at the measurement position, which is synchronously collected by the camera. The collected image is de-phased by using the principle of four-step phase shift and multi-frequency heterodyne to obtain 3D information. The coarse positioning algorithm of the manipulator is used to splice part of the acquired 3D information, and finally the complete 3D point cloud data on the surface of the workpiece to be measured is obtained. The experimental results show that the method can effectively and quickly obtain the 3D surface information of the car model, with strong stability and high accuracy.

An Improved Combined Framework of Force Measurement With Friction Model for Harmonic Gear

To obtain accurate output torque of robot joint for torque control, a built-in torque sensor is designed in this paper. In order to enhance the performance of harmonic gear, it is urgent to deal with the key issues in terms of the errors of sensing and positioning, torque ripple interference. To handle these aforementioned key issues, four pairs of symmetrically distributed strain gauges are pasted on the bottom of the flexspline. Then, a precise positioning method based on laser marking is proposed to improve the positioning accuracy of the strain gauges. Moreover, Kalman filter is utilized to reduce torque ripple interference in the output signal of the strain gauges. Additionally, the designed device is evaluated by experimental tests which is conducted on prototype trial production. Synchronously, the relationship between the flexspline torque and the joint output torque is verified and the polynomial is used to represent the relationship of the measured torque for the built-in torque sensor and the standard torque sensor in the static and dynamic conditions. Finally, a friction model is presented and identified. Comprehensive comparative experiments is performed the performance of the build-in torque sensor in terms of estimation accuracy and control and it shows that the designed built-in torque sensor with friction compensation can be improved ten times in comparison with that of without friction compensation in terms of steady state mean error and mean value of measurement error. What is more, this designed build-in torque sensor holds tremendous potential for making the compact and light weight motion joint module, especially for cooperative robot and robotic supernumerary limb.

Decentralized Multi-Robot Information Gathering From Unknown Spatial Fields

We present an incremental scalable motion planning algorithm for finding maximally informative trajectories for decentralized mobile robots. These robots are deployed to observe an unknown spatial field, where the informativeness of observations is specified as a density function. Existing works that are typically restricted to discrete domains and synchronous planning often scale poorly depending on the size of the problem. Our goal is to design a distributed control law in continuous domains and an asynchronous communication strategy to guide a team of cooperative robots to visit the most informative locations within a limited mission duration. Our proposed Asynchronous Information Gathering with Bayesian Optimization (AsyncIGBO) algorithm extends ideas from asynchronous Bayesian Optimization (BO) to efficiently sample from a density function. It then combines them with decentralized reactive motion planning techniques to achieve efficient multi-robot information gathering activities. We provide a theoretical justification for our algorithm by deriving an asymptotic no-regret analysis with respect to a known spatial field. Our proposed algorithm is extensively validated through simulation and real-world experiment results with multiple robots.

New Short Scale to Measure Workers’ Attitudes Toward the Implementation of Cooperative Robots in Industrial Work Settings: Instrument Development and Exploration of Attitude Structure

The implementation of new robotic technology at workplaces is oftentimes accompanied by social and organizational change processes. A new context-specific questionnaire was developed as a diagnostic tool to measure workers’ attitudes toward mobile cooperative manufacturing robots to provide a basis for managerial decisions and interventions—the “Attitudes toward Cooperative Industrial Robots Questionnaire” (ACIR-Q). Two samples, an online sample of 355 German manufacturing workers and a field sample of 201 workers from 4 local manufacturing companies were collected. For a large item pool, exploratory and confirmatory factor analysis was used to identify the attitudinal factor structure. Data showed a combined affective-behavioral factor and two cognitive factors on task-related and social-related beliefs. Based on this, the 12-item short scale ACIR-Q was derived using ant colony optimization. As attitudes can also be interpreted as networks of evaluative responses, network analysis was used for further insights. The small-world network structure (high clustering and connectivity) allows to hold complex attitudes and centrality measures indicate the most influential evaluative responses. Additionally, we explored relationships between workers’ attitudes and interpersonal variables (perceived competence, perceived control, and general self-efficacy), as well as social/organizational variables (trust in management, support climate, job insecurity and job characteristics). Based on the results, practical implications are suggested to improve workers’ attitudes.

Hand Gesture Interface for Robot Path Definition in Collaborative Applications: Implementation and Comparative Study.

The article explores the possibilities of using hand gestures as a control interface for robotic systems in a collaborative workspace. The development of hand gesture control interfaces has become increasingly important in everyday life as well as professional contexts such as manufacturing processes. We present a system designed to facilitate collaboration between humans and robots in manufacturing processes that require frequent revisions of the robot path and that allows direct definition of the waypoints, which differentiates our system from the existing ones. We introduce a novel and intuitive approach to human-robot cooperation through the use of simple gestures. As part of a robotic workspace, a proposed interface was developed and implemented utilising three RGB-D sensors for monitoring the operator's hand movements within the workspace. The system employs distributed data processing through multiple Jetson Nano units, with each unit processing data from a single camera. MediaPipe solution is utilised to localise the hand landmarks in the RGB image, enabling gesture recognition. We compare the conventional methods of defining robot trajectories with their developed gesture-based system through an experiment with 20 volunteers. The experiment involved verification of the system under realistic conditions in a real workspace closely resembling the intended industrial application. Data collected during the experiment included both objective and subjective parameters. The results indicate that the gesture-based interface enables users to define a given path objectively faster than conventional methods. We critically analyse the features and limitations of the developed system and suggest directions for future research. Overall, the experimental results indicate the usefulness of the developed system as it can speed up the definition of the robot's path.

Development of a Novel Spherical Light-Based Positioning Sensor in Solar Tracking.

Tracking of the sun, which increases the efficiency of solar energy production systems, has shown considerable development in recent years. This development has been achieved by custom-positioned light sensors, image cameras, sensorless chronological systems and intelligent controller supported systems or by synergetic use of these systems. This study contributes to this research area with a novel spherical-based sensor which measures spherical light source emittance and localizes the light source. This sensor was built by using miniature light sensors placed on a spherical shaped three-dimensional printed body with data acquisition electronic circuitry. Besides the developed sensor data acquisition embedded software, preprocessing and filtering processes were conducted on these measured data. In the study, the outputs of Moving Average, Savitzky-Golay, and Median filters were used for the localization of the light source. The center of gravity for each filter used was determined as a point, and the location of the light source was determined. The spherical sensor system obtained by this study is applicable for various solar tracking methods. The approach of the study also shows that this measurement system is applicable for obtaining the position of local light sources such as the ones placed on mobile or cooperative robots.

Human–Robot Cooperation in Economic Games: People Show Strong Reciprocity but Conditional Prosociality Toward Robots

Understanding how people socially engage with robots is becoming increasingly important as these machines are deployed in social settings. We investigated 70 participants’ situational cooperation tendencies towards a robot using prisoner’s dilemma games, manipulating the incentives for cooperative decisions to be high or low. We predicted that people would cooperate more often with the robot in high-incentive conditions. We also administered subjective measures to explore the relationships between people’s cooperative decisions and their social value orientation, attitudes towards robots, and anthropomorphism tendencies. Our results showed incentive structure did not predict human cooperation overall, but did influence cooperation in early rounds, where participants cooperated significantly more in high-incentive conditions. Exploratory analyses further revealed that participants played a tit-for-tat strategy against the robot (whose decisions were random), and only behaved prosocially toward the robot when they had achieved high scores themselves. These findings highlight how people make social decisions when their individual profit is at odds with collective profit with a robot, and advance understanding on human–robot interactions in collaborative contexts.

Applying Digital Twin and Multi-Adaptive Genetic Algorithms in Human–Robot Cooperative Assembly Optimization

In this study, we utilized digital twin technology in combination with genetic algorithms to optimize human–robot cooperation in a miniature light bulb assembly production line. First, the digital twin was used to find the robot’s motion trajectory; a digital replica of the assembly system and human was created by combining sensors that track the position and activity characteristics of the human in the workspace, which helped to prevent human–robot conflicts. Then, a multi-adaptive genetic algorithm was applied to calculate optimal ergonomics and create a worker’s movement schedule. To ensure continuous operation and no shortage of materials, the worker must observe and move to the input conveyor and material pallets to supply materials to the system. It aimed to provide more input materials for the assembly line while allowing the worker’s task to take place in parallel with the robotic assembly operation. The algorithm was designed to reduce the number of moves required to obtain materials and to ensure that the robot always had enough materials to assemble along the defined trajectory, thus, saving labor and optimizing the manufacturing process. The combination of a digital twin and multi-adaptive genetic algorithm optimized the robot’s movement path and the number of movements performed by the human operator in parallel.

Sliding mode controller for a hybrid lower limb rehabilitation robot with fuzzy adjustment of impedance interaction: A patient cooperation approach

In this study, a sliding mode controller with an adaptive fuzzy impedance model is proposed to improve the human–robot cooperation and promote lower limb rehabilitation performance using a hybrid robot including an orthosis and a programmable plate, designed and built at the University of Guilan. Orthosis controls the patient in the path of the joints, and the plate is considered instead of a treadmill to prevent impact on the soles of the feet. Since the patient’s cooperation to regain motor skills is of particular importance in the training process, the proposed controller tracks the path of the joints while considering the patient will. The controller consists of an adaptive impedance control whose coefficients are adjusted using a fuzzy logic. In fact, the impedance model defines the relationship between the robot and subject. Using the model, the subject force is converted to a virtual displacement and, then, added to the tracking error, then a sliding mode controller tracks the modified path. Moreover, the Lyapunov function is used to guaranty the stability and the sign function which depends on the patient cooperation. To evaluate the performance of the proposed method, the control model is implemented on a healthy person and, then, is compared with the sliding mode controller and constant impedance sliding mode controller. The results show that this method while following the path of joints is able to consider the subject cooperation and overcome nonlinear terms while chattering is low.

Automatic Calibration of Tool Center Point for Six Degree of Freedom Robot

The traditional tool center point (TCP) calibration method requires the operator to use their experience to set the actual position of the tool center point. To address this lengthy workflow and low accuracy, while improving accuracy and efficiency for time-saving and non-contact calibration, this paper proposes an enhanced automatic TCP calibration method based on a laser displacement sensor and implemented on a cooperative robot with six degrees of freedom. During the calibration process, the robot arm will move a certain distance along the X and Y axes and collect the information when the tool passes through the laser during the process to calculate the runout of the tool, and then continue to move a certain distance along the X and Y axes for the second height calibration. After the runout angle is calculated and calibrated by triangulation, the runout calibration is completed and the third X and Y axis displacement is performed to find out the exact position of the tool on the X and Y axes. Finally, the tool is moved to a position higher than the laser, and the laser is triggered by moving downward to obtain information to complete the whole experimental process and receive the calibrated tool center position. The whole calibration method is, firstly, verified in the virtual simulation environment and then implemented on the actual cooperative robot. The results of the proposed TCP calibration method for the case of using a pin tool can achieve a positioning deviation of 0.074 and 0.125 mm for the robot moving speeds of 20 and 40 mm/s, respectively. The orientation deviation in the x-axis are 0.089 and −0.184 degrees for the robot moving speeds of 20 and 40 mm/s, respectively. The positioning repeatability of ±0.083 mm for the moving speed of 20 mm/s is lower than ±0.101 mm for the speed of 40 mm/s. It shows that lower moving speed can obtain higher accuracy and better repeatability. This result meets the requirements of TCP calibration but also achieves the purpose of being simple, economical, and time-saving, and it takes only 60 s to complete the whole calibration process.

Multi-Robot Collaborative Flexible Manufacturing and Digital Twin System Design of Circuit Breakers

Circuit breakers (CBs) are mainly designed to interrupt current flow when faults are detected and have been widely used in industrial applications. The existing CBs manufacturing method is semi-automatic and requires a lot of labor. To realize flexible manufacturing, a multi-robot cooperative CBs flexible manufacturing system (CBFMS) is presented in this study. Aiming at the efficiency of the multi-robot cooperative CBFMS key units, a two-arm cooperation robot approach is proposed. The reinforcement learning algorithm is developed to optimize the manufacturing trajectory of the two-arm cooperation robot. To build and optimize the multi-robot cooperative CBFMS, a digital twin (DT) system describing all physical properties of the physical manufacturing plant is constructed for simulation. In the developed DT system, a kinematic control model of the collaboration robot is established. A real-time display of the robot’s trajectory, manufacturing status, and process manufacturing is provided by the data interaction with the physical cell flow between the units. Following this design, a synchronous mapping between the flexible manufacturing DT system of the CBs and the physical workshop is realized, which enables real-time monitoring and management of the physical production line. The experiments’ results show that the manufacturing efficiency, compared with traditional CBs production, is improved by 22%. Moreover, the multi-robot cooperative CBFMS can make process changes according to the production requirements, which can improve the stability of production.

From animal collective behaviors to swarm robotic cooperation.

The collective behaviors of animals, from schooling fish to packing wolves and flocking birds, display plenty of fascinating phenomena that result from simple interaction rules among individuals. The emergent intelligent properties of the animal collective behaviors, such as self-organization, robustness, adaptability and expansibility, have inspired the design of autonomous unmanned swarm systems. This article reviews several typical natural collective behaviors, introduces the origin and connotation of swarm intelligence, and gives the application case of animal collective behaviors. On this basis, the article focuses on the forefront of progress and bionic achievements of aerial, ground and marine robotics swarms, illustrating the mapping relationship from biological cooperative mechanisms to cooperative unmanned cluster systems. Finally, considering the significance of the coexisting-cooperative-cognitive human-machine system, the key technologies to be solved are given as the reference directions for the subsequent exploration.

A Lyapunov-based robust control for permanent magnet synchronous motor in the modular joint of collaborative robot

AbstractIn order to decrease the influence of system parameters and load on the dynamic performance of permanent magnet synchronous motor (PMSM) in cooperative robot joint modules, a practical model-based robust control method was proposed. It inherits the traditional proportional-integral-derivative (PID) control and robust control based on error and model-based control. We first set up the nominal controller using the dynamics model. In order to limit the influence of uncertainty on dynamic performance, a robust controller is established based on Lyapunov method. The control can be regarded as an improved PID control or a redesigned robust control. Compared with the traditional control method, it is simple to implement and has practical effects. It is proved by theoretical analysis that the controller can guarantee the uniform boundedness and uniform final boundedness of the system. In addition, the prototype of fast controller cSPACE is built on the experiment platform, which averts long-time programming and debugging. It offers immense convenience for practical operation. Finally, numerical simulation and real-time experiment results are presented. Based on cSPACE and a PMSM in the joint module of a practical cooperative robot, the availability of the control design and the achievable control performance are verified.

Adaptive Learning-Based Distributed Control of Cooperative Robot Arm Manipulation for Unknown Objects

This article proposes a distributed cooperative manipulation control scheme for multirobot systems to track reference trajectories with unknown payload dynamics, grasp positions, and external disturbances. An online learning module is established to estimate the payload dynamics. Then a wrench-synthetic trajectory tracking control protocol is thereby developed to manipulate an object under unknown external disturbances no matter where the grasping points are. Moreover, sufficient conditions are derived to guarantee the uniform boundedness of the tracking errors of the closed-loop cooperative manipulation system. Finally, numerical simulations are conducted to substantiate the effectiveness of the proposed cooperative manipulation control scheme.

Cooperative human–robot polishing for the task of patina growing on high-quality leather shoes

A patina is essentially the weathered look a piece of leather takes on as it ages. The patina finishing aspect can be also generated or grown artificially by scrubbing the leather surface with specific products. These kinds of manual finishing operations on small objects are delicate and regularly need slight corrections carried out by skilled artisans, which adds complexity to the process automation and implies various key aspects to consider. This research presents a novel approach for automatic and semiautomatic shoe patina growing in the footwear industry using a new co-creative method based on cooperative robotics. The system automates the process in pursuit of operator time-saving without reducing the work finishing quality. For this purpose, the use of a collaborative robot with a built-in constant contact force control and a collaborative tool are used in this research. The use of both tools in complementarity with the knowledge of the craftsman leads the robot end-effector adaptation to the inherent curved surfaces over the shoe. Besides, some orientation corrections are applied based on the CAD model for the task to be accurately accomplished. The solution has been successfully integrated in a real production line, and it is currently in use.

A System-Dynamic Model for Human–Robot Interaction; Solving the Puzzle of Complex Interactions

Cooperative robots in the workspace have an effect on safety that is not yet fully understood. This work collates pre-existing knowledge on human, technological and organizational factors for human-robot interaction and develops a system dynamics model that captures the complex interactions. Expert consultation in the form of a Delphi study is used to derive a tractable model from pre-existing puzzle pieces. A final model is presented, which contains 10 nodes and 20 relationships containing the three key outcome factors of human-robot interaction, viz. Safety, Efficiency and Sustainability. By combining these factors into a single tractable framework, this model bridges the gap between individual efforts from previous works in the field of robotics.

SROS2 with OIDC（OpenID Connect）—サービスロボットに対する命令の信頼性を担保する技術

More robots are involved with humans, such as cooperative robots. When providing services based on user attributes (name, authority, location information, etc.) or authentication (face, fingerprints, etc.), developers must be careful to protect personal information. Therefore, we developed and released a package called “sros2_oidc”. The app adopts the OIDC (OpenID Connect) as an authentication protocol. It is one of the standard authentication protocols for online services. And combined with SROS2, personal information is sent through a secure route to the end of the robots.

Zaufanie – istotny czynnik w human–robot collaboration

Purpose – The purpose of this article is to present factors affecting the quality of human–robot collaboration (HRI) in the workplace. The impact of trust is described in detail. According to the Polish Economic Institute, between 1993 and 2018, the number of industrial robots in the world increased from 557,000 to 2.4 million. Implemented robots, cease to be just tools in human hands. Thanks to their autonomy, they are becoming known as teammates. Research method – The article is based on a literature review conducted to identify factors, particularly trust, that affect human–robot collaboration. Results – It has been revealed that research conducted in the HRI area proves that human trust in robots, is one of the most important determinants of proper cooperation. Above that, the relevance of areas such as reliability, predictability of robots, the personality of people, or appearance of robots was pointed out. The mentioned areas have a direct impact on the formation and level of trust in human–robot teams. Originality / value / implications / recommendations – The publication highlights the relevance of the area of human–robot collaboration (HRC), as part of the implementation of robots in modern enterprises. The article details which elements in the formation of HRC play the most important role. The topic of HRC is vaguely known in Poland, and as the referenced literature indicates, the correct cooperation of humans and robots is an important element affecting the success of robotization. Learning how HRC works is one of the challenges facing today’s organizations.

Review of Technology, Application Status and Development Trend in Multi-arm Cooperative Robots

Review of Technology, Application Status and Development Trend in Multi-arm Cooperative Robots