Robotic Mounted Rail Arm System for implementing effective workplace safety for migrant workers.

Edge intelligence and agnostic robotic paradigm in resource synchronisation and sharing in flexible robotic and facility control system

There is a missing link between a virtual development environment (e.g., a CAD/CAM driven offline robotic programming) and production requirements of the actual robotic workcell. Simulated robot path planning and generation of pick-and-place coordinate points will not exactly coincide with the robot performance due to lack of consideration in variations in individual robot repeatability and thermal expansion of robot linkages. This is especially important when robots are controlled and programmed remotely (e.g., through Internet or Ethernet) since remote users have no physical contact with robotic systems. Using the current technology in Internet-based manufacturing that is limited to a web camera for live image transfer has been a significant challenge for the robot task performance. Consequently, the calibration and accuracy quantification of robot critical to precision assembly have to be performed on-site and the verification of robot positioning accuracy cannot be ascertained remotely. In worst case, the remote users have to assume the robot performance envelope provided by the manufacturers, which may causes a potentially serious hazard for system crash and damage to the parts and robot arms. Currently, there is no reliable methodology for remotely calibrating the robot performance. The objective of this research is, therefore, to advance the current state-of-the-art in Internet-based control and monitoring technology, with a specific aim in the accuracy calibration of micro precision robotic system for the development of a novel methodology utilizing Ethernet-based smart image sensors and other advanced precision sensory control network.

This thesis addresses stable inversion based output tracking control and its applications to robotic systems. It considers the non-causal invertibility (stable inversion) problem of control systems in its various aspects including properties of stable inverses and algorithms for constructing stable inverses. Then, the stable inversion approach is applied to solve a control problem of long-standing interest: output tracking control for non-minimum phase nonlinear systems. A minimum energy property of stable inverses is firstly established. The property claims that given any desired output trajectory, out of infinitely many possible inverse solutions, the one provided by the stable inversion process is the only one that has finite energy. Based on this property, a numerical procedure is developed to provide an efficient approach to construct stable inverses. Secondly, a new output tracking control design is developed. The design incorporates stable inverses and assumes a controller structure of feed-forward plus feedback. It achieves high precision tracking together with closed-loop stability. Furthermore, when system uncertainties are considered and assumed to satisfy the so-called matching conditions, a modified controller structure is presented and the corresponding robust tracking performance is discussed. Finally, the stable inversion based tracking control design is applied to three flexible robotic systems. The first study is output tracking control of a flexible-joint robot. The application demonstrates how the new design deals with the undesirable non-minimum phase property and achieves desired output tracking. The second application is tip trajectory tracking for a two-flexible-link manipulator. This thesis, for the first time, addresses the problem of stable tip trajectory tracking without any transient or steady-state errors for such non-minimum phase systems. In the third application, a new optimal motion control strategy for a flexible space robot is presented. The space robot system is assumed to consist of a two-link flexible manipulator attached to rigid space-craft. Optimality is in the sense that a performance index measured by maneuvering time, control effort, and structural vibrations is minimized while the interference from the manipulator to spacecraft is kept satisfactorily small. Studies on three applications demonstrate that the stable inversion based control design is very effective on output tracking for various robotic systems. This approach is expected to perform equivalently well for many other realistic non-minimum phase nonlinear systems.

<div class="htmlview paragraph">In this investigation a robotic system's dynamic performance is optimized for high reliability under uncertainty. The dynamic capability equations allow designers to predict the dynamic performance of a robotic system for a particular configuration (i.e.,point design). While the dynamic capability equations are a powerful tool, they can not account for performance variations due to aleatory uncertainties inherent in the system. To account for the inherent aleatory uncertainties, a reliability-based design optimization (RBDO) strategy is employed to design robotic systems with robust dynamic performance. RBDO has traditionally been implemented as a nested multilevel optimization process in which reliability constraints require solution to an optimization problem (i.e., reliability analysis). In this work a robust unilevel performance measure approach(PMA) is developed for performing reliability-based design optimization which eliminates the lower level problem in RBDO. A robotic test problem is used to illustrate the efficacy of the approach.</div>

This study explores the incorporation of time-varying sign gain into a parallel iterative learning control (ILC) architecture, augmented by an expert system, to enhance the performance and stability of a robotic arm system. The methodology involves iteratively tuning the learning control gains using time-varying sign gain guided by an expert system. Stability analysis, encompassing asymptotic and monotonic convergence, demonstrates promising results across multiple joints, affirming the effectiveness of the proposed control architecture. In comparison with traditional PID control, fixed gain ILC, and ILC with adaptive learning in the expert system, the analysis focuses on stability, precision, and adaptability, using root mean square error (RMSE) as a key metric. The results show that ILC with adaptive learning from the expert system consistently reduces RMSE, even in the presence of learning transients. This adaptability effectively controls the learning transients, ensuring improved performance in subsequent iterations. In conclusion, the integration of time-varying sign gain with expert system assistance in a parallel ILC architecture holds promise for advancing adaptive control in robotic systems. Positive outcomes in stability, precision, and adaptability suggest practical applications in real-world scenarios. This research provides valuable insights into the implementation of dynamic learning mechanisms for enhanced robotic system performance, laying the groundwork for future refinement in robotic manipulator control systems.

The main field of our research is artificial intelligence already implemented in the experimental autonomous road vehicle. Artificial intelligence now is a really huge area of studies. This investigation is focused more on a development of intelligent systems. Such as expert systems, semantic text processing systems, semantic image understanding systems, robotics systems. Wi!Mi is a solution for developing mivar knowledge models. This tool belongs to the class of so-called ES shells - programs that allow significantly simplify and accelerate the ES development process. It uses a novel knowledge representation mechanism based on bipartite graphs and the significantly improved but simple inference engine, which is able to process large systems involving millions of variables in just a few seconds. A special representation model which is called mivar nets with linear computational complexity using if-then rules is used in Wi!Mi. The idea is that the subject domain is divided into objects and connections between them. Scientific investigation allows to implement new decision-making system called “RoboRazum” as a form of an embedded software platform with flexible capabilities to adapt to control by any robotic suites and systems. RoboRazum is a platform for designing autonomous robotic control systems. Provided solutions don’t require powerful computational resources and could be used in small systems-on-chip like microcontrollers. That is why this solution is perfectly fit with conception of Internet of Things (IoT). Reasoned and fast logical decisions based on mivar technologies play important role for autonomous road vehicles.

Robotic systems have significantly transformed the landscape of minimally invasive surgery, offering enhanced precision, reduced recovery times, and improved patient outcomes. These systems have evolved from simple mechanical tools to sophisticated platforms integrating advanced control algorithms and real-time feedback mechanisms. This paper provides a comprehensive overview of the role of robotic systems in minimally invasive surgery, exploring the various benefits, inherent risks, and the challenges associated with their adoption and development. We examine the technical aspects of robotic control systems, such as kinematics, force control, and haptic feedback, which enable greater surgical accuracy. Despite these advantages, challenges such as system complexity, high costs, and ethical concerns remain significant barriers to widespread adoption. The future of robotic surgery lies in overcoming these obstacles, with advancements in system miniaturization and further refinement of control systems poised to enhance the efficacy and accessibility of robotic platforms. This paper explores the role of robotic systems in minimally invasive surgery, focusing on three key areas: bronchoscopy and ureteroscopy. By reviewing the benefits, risks, case studies, and future directions of these technologies, the paper seeks to provide an in-depth understanding of how robotic systems are shaping the future of surgery. Key words: Robotic Surgery, Minimally Invasive Surgery, Robotic Control Systems, Surgical Precision, PID Control, Kinematics, Inverse Kinematics, Forward Kinematics, Dynamic Control, Force Control, Impedance Control, Surgical Robotics, Haptic Feedback, Robotic Arm, Robotic Surgery Benefits, Robotic Surgery Risks, Robot-Assisted Surgery, Surgeon Console, Real-Time Feedback, Surgical Training, Robotic System Development, System Testing, Clinical Trials, Surgical Robot Performance, Robotics in Urology, Telepresence Surgery, Robotic Surgery Cost, Robotic Surgery Future Directions.

This study aims to enhance the accuracy and efficiency of Omni robots in navigation, reducing errors and resource use to improve safety and task completion in various applications. Utilizing CoppeliaSim (Vrep) for simulation, the research focuses on the Omni robot's performance over homogeneous and non-homogeneous paths using SLAM. Key parameters such as running time, average velocity, body change, and error are analyzed with statistical methods to ensure robust findings. Results show a direct relationship between speed and tracking error, highlighting the need for optimized speed management. The study provides insights into the robot's performance under different conditions, offering valuable data for further optimization. This research contributes to the development of safer, more reliable robotic systems with applications in industrial automation, healthcare, and service robotics. Virtual prototyping reduces development costs and risks, promoting the adoption of advanced robotic technologies and enhancing productivity and safety in various fields.

There have been a lot of works on the improvement of the robotic performance. Nowadays a robot can work well under given constraints and environments. But the performance of a single robot might be limited and some needs more complex performance. To cope with the complex works, there are several approaches, such as more sophistication of a single robot and multiple robotics with different levels of capacities. In this paper, the multiple robotic system approach will show more flexibility and adaptability to various tasks and environments. The robots with different capacities, such as Cellular Robotic System (CEBOT), are one of the distributed autonomous robotic systems and consist of the heterogeneous system, thus can create intelligence for wider tasks. This paper describes these characteristics of the robotic system depending on the level.

Abrasion and blunt tissue trauma study of a novel flexible robotic system in the porcine model

In this investigation a robotic system's dynamic performance is optimized for high reliability under uncertainty. The dynamic capability equations (DCE) allow designers to predict the dynamic performance of a robotic system for a particular configuration and reference point on the end-effector (i.e.,point design). Here the DCE are used in conjunction with a reliability-based design optimization (RBDO) strategy in order to obtain designs with robust dynamic performance with respect to the end-effector reference point. In this work a unilevel performance measure approach (PMA) is used to perform RBDO. This is important for the reliable design of robotic systems in which a solution to the DCE is required for each constraint call. The method is illustrated on a robot design problem

A robot arm is a mechanism for positioning parts or tools with a consistent accuracy and at a speed that makes the robot cost-effective. So a robot’s performance is primarily measured in terms of its accuracy and its speed, although it is not maximum speed but cycle time that is the important factor. (Cycle time is the time to carry out one complete cycle of operations.)

Digital and mechatronic methods, paired with artificial intelligence and machine learning, are transformative technologies in behavioral science and biology. The central element of the most important pollinator species-honey bees-is the colony's queen. Because honey bee self-regulation is complex and studying queens in their natural colony context is difficult, the behavioral strategies of these organisms have not been widely studied. We created an autonomous robotic observation and behavioral analysis system aimed at continuous observation of the queen and her interactions with worker bees and comb cells, generating behavioral datasets of exceptional length and quality. Key behavioral metrics of the queen and her social embedding within the colony were gathered using our robotic system. Data were collected continuously for 24 hours a day over a period of 30 days, demonstrating our system's capability to extract key behavioral metrics at microscopic, mesoscopic, and macroscopic system levels. Additionally, interactions among the queen, worker bees, and brood were observed and quantified. Long-term continuous observations performed by the robot yielded large amounts of high-definition video data that are beyond the observation capabilities of humans or stationary cameras. Our robotic system can enable a deeper understanding of the innermost mechanisms of honey bees' swarm-intelligent self-regulation. Moreover, it offers the possibility to study other social insect colonies, biocoenoses, and ecosystems in an automated manner. Social insects are keystone species in all terrestrial ecosystems; thus, developing a better understanding of their behaviors will be invaluable for the protection and even the restoration of our fragile ecosystems globally.

Transoral endoscopic head and neck surgery now plays an important role in the multidisciplinary management of oropharyngeal carcinoma. Previous generations of robotic surgical systems used a multiport system with a rigid stereo-endoscope and 2 wristed instruments that facilitated transoral robotic surgery. To evaluate a new single-port robotic surgical system in head and neck surgery prospectively through concurrent nonrandomized clinical trials. Two prospective clinical trials were conducted from December 16, 2016, to December 26, 2017, to assess the safety, feasibility, and performance of a flexible single-port robotic surgical system in 4 institutions, including 3 in the United States and 1 in Hong Kong. A total of 47 patients with tumors of the oropharynx were enrolled and underwent surgery. All patients were classified as having American Society of Anesthesiologists class I to III status and Eastern Cooperative Oncology Group status 0 to 1. An initial cohort of 7 patients underwent staging and endoscopic procedures for benign disease. The remaining 40 patients all had malignant tumors of the oropharynx. Safety was measured by the incidence of device-related serious adverse events. Feasibility and performance were measured by the conversion rate from the use of the single-port robotic surgical system to either open surgery or the use of any other transoral technology required to complete the planned procedure. Secondary end points of swallowing function and surgical margins were also measured. All 47 patients (8 women and 39 men; mean [SD] age, 61 [8] years) safely underwent transoral resection with the single-port robotic surgical system without conversion to open surgery, laser surgery, or multiport robotic surgery. There were no intraoperative complications or device-related serious adverse events. Mean (SD) estimated intraoperative blood loss per procedure was 15.4 (23.9) mL; no patients received a transfusion. Two patients underwent a planned tracheotomy owing to medical comorbidity (previous chemoradiotherapy; obesity and severe sleep apnea). Two patients (4%) had grade III or IV postoperative hemorrhage, requiring a return to the operating room; however, both patients had medical comorbidities requiring the use of antithrombotic medication. The incidence of positive margins for patients with oropharyngeal malignancy was 3% (1 of 40). Within 30 days, 45 patients (96%) were eating by mouth and without the need for a percutaneous endoscopic gastrostomy tube. This study describes the results of phase 2 clinical testing of a next-generation, robotic surgical system using a single-port architecture. The use of the device appears to be feasible, safe, and effective for transoral robotic surgery of oropharyngeal tumors. ClinicalTrials.gov identifiers: NCT03010813 and NCT03049280.

Robots capable of manipulating cohesive materials would be beneficial in a variety of complex construction tasks. To discover principles by which robotic systems can effectively manipulate entangled granular media, we develop a robophysical platform for interaction with media composed of u-shaped particles. This robotic platform uses environmental signals to autonomously coordinate excavation, transport, and deposition of material. We test the effect of material initial conditions by characterizing robot performance in two different material compaction states, and observe as much as a 75% change in transported mass depending on initial material compressive loading. This large difference suggests the functional role that properties such as packing and geometric cohesion play in excavation and manipulation. To better understand these properties, we develop an apparatus for tensile testing of the geometrically cohesive media, which reveals how entangled material strength depends strongly on initial compressive loading. These results rationalize the variation observed in robotic performance and point to future directions for better understanding robotic interaction with entangled materials.