Search Results (12)

The ability to autonomously generate up-to-date 3D models of robotic workcells is critical for advancing smart manufacturing, yet existing Next-Best-View (NBV) methods often rely on paradigms ill-suited for the fixed-base manipulators found in dynamic industrial environments. To address this gap, this paper proposes a novel NBV method for the complete exploration of a 6-DOF robotic arm’s workspace. Our approach integrates collision-based information gain metric, a potential field technique to generate candidate views from exploration frontiers, and a tunable fitness function to balance information gain with motion cost. The method was rigorously tested in three simulated scenarios and validated on a physical industrial robot. Results demonstrate that our approach successfully maps the majority of the workspace in all setups, with a balanced weighting strategy proving most effective for combining exploration speed and path efficiency, a finding confirmed in the real-world experiment. We conclude that our method provides a practical and robust solution for autonomous workspace mapping, offering a flexible, training-free approach that advances the state-of-the-art for on-demand 3D model generation in industrial robotics. Full article

In the context of Industry 5.0, human–robot collaboration (HRC) is increasingly crucial for enabling safe and efficient operations in shared industrial workspaces. This study aims to implement a hybrid robotic architecture based on the Speed and Separation Monitoring (SSM) collaborative scenario defined in ISO/TS 15066. The system calculates the minimum protective separation distance between the robot and the operators and slows down or stops the robot according to the risk assessment computed in real time. Compared to existing solutions, the approach prevents collisions and maximizes workcell production by reducing the robot speed only when the calculated safety index indicates an imminent risk of collision. The proposed distributed software architecture utilizes the ROS2 framework, integrating three modules: (1) a fast and reliable human tracking module based on the OptiTrack system that considerably reduces latency times or false positives, (2) an intention estimation (IE) module, employing a linear Kalman filter (LKF) to predict the operator’s next position and velocity, thus considering the current scenario and not the worst case, and (3) a robot control module that computes the protective separation distance and assesses the safety index by measuring the Euclidean distance between operators and the robot. This module dynamically adjusts robot speed to maintain safety while minimizing unnecessary slowdowns, ensuring the efficiency of collaborative tasks. Experimental results demonstrate that the proposed system effectively balances safety and speed, optimizing overall performance in human–robot collaborative industrial environments, with significant improvements in productivity and reduced risk of accidents. Full article

Multi-camera systems are an effective solution for perceiving large areas or complex scenarios with many occlusions. In such a setup, an accurate camera network calibration is crucial in order to localize scene elements with respect to a single reference frame shared by all the viewpoints of the network. This is particularly important in applications such as object detection and people tracking. Multi-camera calibration is a critical requirement also in several robotics scenarios, particularly those involving a robotic workcell equipped with a manipulator surrounded by multiple sensors. Within this scenario, the robot-world hand-eye calibration is an additional crucial element for determining the exact position of each camera with respect to the robot, in order to provide information about the surrounding workspace directly to the manipulator. Despite the importance of the calibration process in the two scenarios outlined above, namely (i) a camera network, and (ii) a camera network with a robot, there is a lack of standard datasets available in the literature to evaluate and compare calibration methods. Moreover they are usually treated separately and tested on dedicated setups. In this paper, we propose a general standard dataset acquired in a robotic workcell where calibration methods can be evaluated in two use cases: camera network calibration and robot-world hand-eye calibration. The Multi-Eye To Robot Indoor Calibration (METRIC) dataset consists of over 10,000 synthetic and real images of ChAruCo and checkerboard patterns, each one rigidly attached to the robot end-effector, which was moved in front of four cameras surrounding the manipulator from different viewpoints during the image acquisition. The real images in the dataset includes several multi-view image sets captured by three different types of sensor networks: Microsoft Kinect V2, Intel RealSense Depth D455 and Intel RealSense Lidar L515, to evaluate their advantages and disadvantages for calibration. Furthermore, in order to accurately analyze the effect of camera-robot distance on calibration, we acquired a comprehensive synthetic dataset, with related ground truth, with three different camera network setups corresponding to three levels of calibration difficulty depending on the cell size. An additional contribution of this work is to provide a comprehensive evaluation of state-of-the-art calibration methods using our dataset, highlighting their strengths and weaknesses, in order to outline two benchmarks for the two aforementioned use cases. Full article

The automation of bin-picking processes has been a research topic for almost two decades. General-purpose equipment, however, still does not show adequate success rates to find application in most industrial tasks. Human–robot collaboration in bin–picking tasks can increase the success rate by exploiting human perception and handling skills and the robot ability to perform repetitive tasks. The aim of this paper, starting from a general-purpose industrial bin picking equipment comprising a 3D–structured light vision system and a collaborative robot, consists in enhancing its performance and possible applications through human–robot collaboration. To achieve successful and fluent human–robot collaboration, the robotic workcell must meet some hardware and software requirements that are defined below. The proposed strategy is tested in some sample tests: the results of the experimental tests show that collaborative functions can be particularly useful to overcome typical bin picking failures and to improve the fault tolerance of the system, increasing its flexibility and reducing downtimes. Full article

The paper describes a method for planning collision-free motions of an industrial manipulator that shares the workspace with human operators during a human–robot collaborative application with strict safety requirements. The proposed workflow exploits the advantages of mixed reality to insert real entities into a virtual scene, wherein the robot control command is computed and validated by simulating robot motions without risks for the human. The proposed motion planner relies on a sensor-fusion algorithm that improves the 3D perception of the humans inside the robot workspace. Such an algorithm merges the estimations of the pose of the human bones reconstructed by means of a pointcloud-based skeleton tracking algorithm with the orientation data acquired from wearable inertial measurement units (IMUs) supposed to be fixed to the human bones. The algorithm provides a final reconstruction of the position and of the orientation of the human bones that can be used to include the human in the virtual simulation of the robotic workcell. A dynamic motion-planning algorithm can be processed within such a mixed-reality environment, allowing the computation of a collision-free joint velocity command for the real robot. Full article

A two-dimensional (2-D) camera system with a real-time image processing-based safety technology is a cost-effective alternative that needs optimization of the cell layout, the number of cameras, and the camera’s locations and orientations. A design optimization study was performed using the multi-criteria linear fractional programming method and considering the number of cameras, the resolution, as well as camera positions and orientations. A table-top experimental setup was designed and built to test the effectiveness of the optimized design using two cameras. The designs at optimal and nonoptimal parameters were compared using a deep learning algorithm, ResNet-152. To eliminate blind spots, a simple but novel 2-D image merging technique was proposed as an alternative to commonly employed stereo imaging methods. Verification experiments were conducted by using two camera resolutions with two graphic processors under varying illuminance. It was validated that high-speed entrances to the safety system were detected reliably and with a 0.1 s response time. Moreover, the system was proven to work effectively at a minimum illuminance of 120 lux, while commercial systems cannot be operated under 400 lux. After determining the most appropriate 2-D camera type, positions, and angles within the international standards, the most cost-effective solution set with a performance-to-price ratio up to 15 times higher than high-cost 3-D camera systems was proposed and validated. Full article

In this paper, a new method for the calibration of robotic cell components is presented and demonstrated by identification of an industrial robotic manipulator’s base and end-effector frames in a workplace. It is based on a mathematical approach using a Jacobian matrix. In addition, using the presented method, identification of other kinematic parameters of a robot is possible. The Universal Robot UR3 was later chosen to prove the working principle in both simulations and experiment, with a simple repeatable low-cost solution for such a task—image analysis to detect tag markers. The results showing the accuracy of the system are included and discussed. Full article

There is no doubt that the rapid development in robotics technology has dramatically changed the interaction model between the Industrial Robot (IR) and the worker. As the current robotic technology has afforded very reliable means to guarantee the physical safety of the worker during a close proximity interaction with the IR. Therefore, new forms of cooperation between the robot and the worker can now be achieved. Collaborative/Cooperative robotics is the new branch of industrial robotics which empowers the idea of cooperative manufacturing. Cooperative manufacturing significantly depends on the existence of a collaborative/cooperative robot (cobot). A cobot is usually a Light-Weight Robot (LWR) which is capable of operating safely with the human co-worker in a shared work environment. This is in contrast with the conventional IR which can only operate in isolation from the worker workspace, due to the fact that the conventional IR can manipulate very heavy objects, which makes it so dangerous to operate in direct contact with the worker. There is a slight difference between the definition of collaboration and cooperation in robotics. In cooperative robotics, both the worker and the robot are performing tasks over the same product in the same shared workspace but not simultaneously. Collaborative robotics has a similar definition, except that the worker and the robot are performing a simultaneous task. Gathering the worker and the cobot in the same manufacturing workcell can provide an easy and cheap method to flexibly customize the production. Moreover, to adapt with the production demands in the real time of production, without the need to stop or to modify the production operations. There are many challenges and problems that can be addressed in the cooperative manufacturing field. However, one of the most important challenges in this field is the representation of the cooperative manufacturing environment and components. Thus, in order to accomplish the cooperative manufacturing concept, a proper approach is required to describe the shared environment between the worker and the cobot. The cooperative manufacturing shared environment includes the cobot, the co-worker, and other production components such as the product itself. Furthermore, the whole cooperative manufacturing system components need to communicate and share their knowledge, to reason and process the shared information, which eventually gives the control solution the capability of obtaining collective manufacturing decisions. Putting into consideration that the control solution should also provide a natural language which is human readable and in the same time can be understood by the machine (i.e., the cobot). Accordingly, a distributed control solution which combines an ontology-based Multi-Agent System (MAS) and a Business Rule Management System (BRMS) is proposed, in order to solve the mentioned challenges in the cooperative manufacturing, which are: manufacturing knowledge representation, sharing, and reasoning. Full article

This research combines between two different manufacturing concepts. On the one hand, flow shop scheduling is a well-known problem in production systems. The problem appears when a group of jobs shares the same processing sequence on two or more machines sequentially. Flow shop scheduling tries to find the appropriate solution to optimize the sequence order of this group of jobs over the existing machines. The goal of flow shop scheduling is to obtain the continuity of the flow of the jobs over the machines. This can be obtained by minimizing the delays between two consequent jobs, therefore the overall makespan can be minimized. On the other hand, collaborative robotics is a relatively recent approach in production where a collaborative robot (cobot) is capable of a close proximity cooperation with the human worker to increase the manufacturing agility and flexibility. The simplest case-study of a collaborative workcell is one cobot in cooperation with one worker. This collaborative workcell can be seen as a special case of the shop flow scheduling problem, where the required time from the worker to perform a specific job is unknown and variable. Therefore, during this research, we implement an intelligent control solution which can optimize the flow shop scheduling problem over the previously mentioned case-study. Full article

Self-Organization is a spontaneous trend which exists in nature among different organisms. Self-organization refers to the process where some form of an overall order arises in a group due to the local interaction among the members of this group. In manufacturing, a similar definition of a Reconfigurable Manufacturing System (RMS) can be found. RMS is a system where the production components and functions can be modified, rearranged and/or interchanged in a timely and cost-effective manner to quickly respond to the production requirements. The definition of the RMS concept implies that the self-organization is an important key factor to fulfil that concept. A case study where a cooperation among a variable number of Industrial Robots (IRs) and workers is studied to show the importance of the research problem. The goal of the paper is to offer a suitable generic control and interaction architecture solution model, which obtains the self-organization from the RMS point of view. Ultimately, applying the proposed solution concept to the case study. Full article

Modern manufacturing systems should satisfy emerging needs related to sustainable development. The design of sustainable manufacturing systems can be valuably supported by simulation, traditionally employed mainly for time and cost reduction. In this paper, a multi-purpose digital simulation approach is proposed to deal with sustainable manufacturing systems design through Discrete Event Simulation (DES) and 3D digital human modelling. DES models integrated with data on power consumption of the manufacturing equipment are utilized to simulate different scenarios with the aim to improve productivity as well as energy efficiency, avoiding resource and energy waste. 3D simulation based on digital human modelling is employed to assess human factors issues related to ergonomics and safety of manufacturing systems. The approach is implemented for the sustainability enhancement of a real manufacturing cell of the aerospace industry, automated by robotic deburring. Alternative scenarios are proposed and simulated, obtaining a significant improvement in terms of energy efficiency (−87%) for the new deburring cell, and a reduction of energy consumption around −69% for the coordinate measuring machine, with high potential annual energy cost savings and increased energy efficiency. Moreover, the simulation-based ergonomic assessment of human operator postures allows 25% improvement of the workcell ergonomic index. Full article

This paper presents a technology for robotic assembly of Polymer Electrolyte Membrane Fuel Cells (PEMFCs). We describe the most recent configuration of the end-effector used for robotic assembly of PEMFCs, the robot workcell, the fuel cell components and the method of automated assembling fuel cell stacks. In this second generation of end-effector and workcell designs, the productivity of the automated assembly process and the capability of the robot to assemble larger scale fuel cell stacks have been improved. The advantage of the technology presented here consists in its low cost, its simplicity, in its capability of rapidly assembling fuel cell stacks containing a large number of cells due to a passive compliance system of the end-effector and in its capability of accurately aligning the fuel cell components in the stack. Full article