Advanced Robotic Systems Research Articles

Endoscopic surgery suturing techniques: a randomized study on learning

BackgroundSurgeons have widely adopted endoscopic suturing techniques using conventional laparoscopic instruments and the more advanced robotic systems. The FlexDex is a novel articulating laparoscopic needle driver providing enhanced dexterity in laparoscopic surgery. This study evaluates and compares the learning curve of endoscopic suturing with conventional laparoscopy, the FlexDex and robotic suturing in novices.MethodsParticipants performed a minimal invasive suturing task in three different ways in a randomized order: with a conventional laparoscopic needle driver, using the FlexDex needle driver and third, using the Da Vinci Si surgical system. Primary outcome was suturing task time. Secondary outcome parameters were assessment of suturing quality and workload perception.ResultsA total of 10 novice participants were included and completed a total of 300 sessions. Median (IQR) suturing time of the first 5 sessions was 231 s (188–291) in the laparoscopic group versus 378 s (282–471) in the FlexDex group versus 189 s (160–247) in the DaVinci Si group. The last 5 sessions showed significant reduction of median suturing time of 143 s (120–190), 232 s (180–265) and 172 s (134–199) respectively. Analysis identified that the learning curve for the laparoscopic needle driver and Da Vinci Si was reached in 5 sessions, compared to 8 sessions for the Flexdex. The laparoscopic needle driver and Da Vinci Si showed a significant shorter median suturing time compared to the FlexDex (p = 0.00). The FlexDex quality assessment scores were significantly lower compared to the laparoscopic (p = 0.00) and robotic (p = 0.00) scores and perceived workload remains high for the FlexDex users.ConclusionsEx vivo endoscopic suturing with the FlexDex demonstrated a prolonged learning curve compared to laparoscopic and robotic suturing. The learning curve of the FlexDex is fundamentally different from conventional laparoscopic and robotic instruments. This study provides further insights in the implementation and training of endoscopic suturing techniques.

Reversible Underwater Adhesion for Soft Robotic Feet by Leveraging Electrochemically Tunable Liquid Metal Interfaces.

Soft crawling robots have potential applications for surveillance, rescue, and detection in complex environments. Despite this, most existing soft crawling robots either use nonadjustable feet to passively induce asymmetry in friction to actuate or are only capable of moving on surfaces with specific designs. Thus, robots often lack the ability to move along arbitrary directions in a two-dimensional (2D) plane or in unpredictable environments such as wet surfaces. Here, leveraging the electrochemically tunable interfaces of liquid metal, we report the development of liquid metal smart feet (LMSF) that enable electrical control of friction for achieving versatile actuation of prismatic crawling robots on wet slippery surfaces. The functionality of the LMSF is examined on crawling robots with soft or rigid actuators. Parameters that affect the performance of the LMSF are investigated. The robots with the LMSF prove capable of actuating across different surfaces in various solutions. Demonstration of 2D locomotion of crawling robots along arbitrary directions validates the versatility and reliability of the LMSF, suggesting broad utility in the development of advanced soft robotic systems.

Hysteresis with lonely stroke in artificial muscles: Characterization, modeling, and inverse compensation

Artificial muscles are inherently compliant actuators that exhibit high power density and impressive stroke and force outputs. They have found numerous applications in advanced mechatronic and robotic systems. Termed as lonely stroke, the first quasi-static input–output cycle of artificial muscles is inconsistent with subsequent cycles that are repeatable and exhibit hysteresis. The lonely stroke not only affects the behavior of artificial muscles, but also presents coupling with the subsequent repeatable hysteresis cycles. While lonely stroke has been reported in a number of artificial muscles, existing studies lack systematic experimental characterization procedure. Furthermore, no models or compensation schemes have been proposed. In this work, we propose the first study to systematically characterize, model, and compensate for the hysteresis with lonely stroke property in artificial muscles. The experimental procedure to characterize the hysteresis with lonely stroke behavior is presented. A modeling approach is developed through the expansion of the input range of the Preisach operator, a widely adopted hysteresis model, to physically infeasible region. The effects of such expansion on the model accuracy and computational cost are studied. An iterative algorithm is proposed to compensate for the hysteresis with lonely stroke by approximately inverting the proposed expanded Preisach operator. The effectiveness of the proposed scheme is validated by comprehensive simulation and experimental results. While this study primarily considers super-coiled polymer (SCP) actuators, the proposed model is also validated for several popular artificial muscles.

Improved fault diagnosis algorithm based on artificial immune network model and neighbourhood rough set theory

With the aim to identify new fault diagnosis and advanced robotic systems, this paper first proposes a fault diagnosis algorithm based on an artificial immune network model that can adjust the pruning threshold. Secondly, the algorithm is improved based on neighbourhood rough set theory, in which the relationships among the pruning threshold, misdiagnosis rate, and missed diagnosis rate in the shape space are discussed. In addition, an improved algorithm for adjusting the adaptively pruning threshold based solely on an observation index is described. The simulation experiments show that the algorithm can identify the new fault modes while keeping the misdiagnosis and missed diagnosis rates low.

АЛГОРИТМ ОБНАРУЖЕНИЯ ОБЪЕКТОВ ДЛЯ ОПТИКО-ЭЛЕКТРОННЫХ СИСТЕМ С ОБУЧЕНИЕМ В РЕАЛЬНОМ ВРЕМЕНИ

In order to create a new algorithm for automatic detection of objects with real-time training, astudy of the world scientific groundwork in the field of general-purpose automatic tracking with theability to recognize a tracked object with the potential for application in embedded computing systemsof optoelectronic systems of promising robotic complexes was carried out. Based on the conductedresearch, methods and approaches were selected and tested that allow, with the greatest accuracy,while maintaining high computational efficiency, to provide training of classifiers on the fly(online learning) without a priori knowledge of the type of tracking object and to ensure the subsequentdetection of the original object in the event of its short-term loss. Such methods include a histogramof oriented gradients – a descriptor of key features based on the analysis of the distribution ofthe brightness gradients of the object image. Its use allows you to reduce the amount of informationused without losing key data about the object and to increase the speed of image processing. Thearticle substantiates the choice of one of the real-time classification algorithms that allows solvingthe problem of binary classification – the support vector machine. Due to the high speed of data processingand the need for a small amount of initial training data to construct a separating hyperplane,on the basis of which the classification of objects is done, this method is chosen as the most suitablefor solving the problem. For online training, a modification of the support vector machine methodwas chosen, which implements stochastic gradient descent at each step of the algorithm – Pegasos.The authors of the study carried out the development and semi-natural modeling of the selected algorithm,evaluated the effectiveness of its work in the tasks of detecting an object of interest in real timewith preliminary online training in the process of tracking the object. The developed algorithm hasshown high efficiency in solving the problem and is planned to be implemented as part of a specialsoftware for optoelectronic systems of advanced robotic systems. In the conclusion, proposals arepresented to further improve the accuracy and probability of the object detection by the developedalgorithm, as well as for improving its performance by optimizing calculations.

Complex optimization of construction waste management and its role in the formation of the concept of "sustainable construction»

The article considers the features of complex optimization of construction waste management and defines its role in the formation of the concept of "sustainable construction". The authors note that in order for the construction, demolition and waste management industries to remain competitive in the global market, they must continue developing and implement innovations in the supply chain to improve efficiency, sustainability, and reduce energy, waste, and resource consumption. This requires serious research on intelligent, mobile, and integrated systems. Radically advanced robotic artificial intelligence systems for sorting and processing must be developed with an emphasis on the required reuse of materials and components. Many industries face an uncertain future in which the applicability of today's technological constraints cannot be assumed. The construction industry is likely to be significantly impacted by the capabilities of transformative technologies such as artificial intelligence, additive manufacturing, nanotechnology, virtual reality, and robotics. The application of such technologies presents significant opportunities for this industry.

DEVELOPMENT AND ANALYSIS OF RECONFIGURABLE ROBOTIC END-EFFECTOR FOR MACHINING AND PART HANDLING

Advanced robotic systems are an Industry 4.0 enabler in smart factories. Industrial robotic manipulators require an end-effector to perform tasks. The purpose of this study was to research and develop a reconfigurable robotic end-effector for machining and part handling. The device eliminates the need for separate robots to perform part handling and machining operations. A reconfigurable, dual-purpose design eliminates lengthy end-effector changes. The paper presents the mechanical conceptualisation, detailed design, manufacturing, and testing of the end- effector and spindle system. The concept uses a flexible, cable-driven gripper system in conjunction with a compact, lightweight milling system that is capable of machining non-ferrous metals. The results demonstrate the versatility and high compliance of the gripper. An experimental study revealed the influence that reconfigurability has on the spindle dynamics. The dynamic response of the gripping system was also experimentally examined during machining to evaluate the practicality of a dual-purpose design. Experimentally developed stability lobe diagrams are presented, which characterise the stable operating parameters of the machining system.

Reliability-based routing metric for UAVs networks

<span>As a result of technological advances in robotic systems, electronic sensors, and communication techniques, the production of unmanned aerial vehicle (UAV) systems has become possible. Their easy installation and flexibility led these UAV systems to be used widely in both military and civilian applications. Note that the capability of one UAV is however limited. Nowadays, a multi-UAV system is of special interest due to the ability of its associate UAV members either to coordinate simultaneous coverage of large areas or to cooperate to achieve common goals/targets. This kind of cooperation/coordination requires a reliable communication network with a proper network model to ensure the exchange of both control and data packets among UAVs. Such network models should provide all-time connectivity to avoid dangerous failures or unintended consequences. Thus, the multi-UAV system relies on communication to operate. Flying ad hoc network (FANET) is moreover considered as a sophisticated type of wireless ad hoc network among UAVs which solved the communication problems into other network models. Along with the FANET’s unique features, challenges and open issues are also discussed especially in the routing protocols approach. We will try to present the expected transmission account metric with a new algorithm for reliability. In addition to this new algorithm mechanism, the metric takes into account the relative speed between UAVs, and thus the increase of the fluctuations in links between UAVs has been detected. Accordingly, the results show that the function of the AODV routing protocol with this metric becomes effective in high mobility environments.</span>

A Novel Speech to Mouth Articulation System for Realistic Humanoid Robots

A significant ongoing issue in realistic humanoid robotics (RHRs) is inaccurate speech to mouth synchronisation. Even the most advanced robotic systems cannot authentically emulate the natural movements of the human jaw, lips and tongue during verbal communication. These visual and functional irregularities have the potential to propagate the Uncanny Valley Effect (UVE) and reduce speech understanding in human-robot interaction (HRI). This paper outlines the development and testing of a novel Computer Aided Design (CAD) robotic mouth prototype with buccinator actuators for emulating the fluidic movements of the human mouth. The robotic mouth system incorporates a custom Machine Learning (ML) application that measures the acoustic qualities of speech synthesis (SS) and translates this data into servomotor triangulation for triggering jaw, lip and tongue positions. The objective of this study is to improve current robotic mouth design and provide engineers with a framework for increasing the authenticity, accuracy and communication capabilities of RHRs for HRI. The primary contributions of this study are the engineering of a robotic mouth prototype and the programming of a speech processing application that achieved a 79.4% syllable accuracy, 86.7% lip synchronisation accuracy and 0.1s speech to mouth articulation differential.

Design and Control of Advanced Robotic Systems for Manufacturing and Assembly

Modern industrial processes must now be designed and controlled with advanced robotic systems for manufacture and assembly to increase productivity, accuracy, and flexibility. The main factors involved in creating and overseeing these robotic systems are presented in detail in this work.In the design stage, manipulators, sensors, and end-effectors that are customised for the particular manufacturing or assembly task are chosen and integrated. To ensure accurate and efficient task execution, additional control algorithms and programming techniques are also developed. This covers adaptive control techniques, path optimisation, trajectory planning, and collision avoidance.The real-time monitoring, coordinating, and synchronisation of several robots and their interactions with the environment are the main goals of the control component. The integration of human operators with robotic systems is made possible by centralised or decentralised control frameworks, which promote secure and effective production and assembly procedures.The study also discusses how to improve robotic systems' abilities to handle complicated jobs and adapt to shifting production settings by integrating cutting-edge technologies like machine learning, computer vision, and augmented reality.The difficulties and possibilities posed by the application of sophisticated robotic systems for manufacturing and assembly are also covered. These include the dependability of the system, the ethical effects of automation in the workplace, the detection and recovery of faults, and human-robot collaboration.The ultimate goal of this work is to give readers a thorough grasp of the design and control principles required for creating advanced robotic systems for manufacturing and assembly, hence promoting higher levels of productivity, quality, and adaptability in industrial settings.

Visual servo guided cyber-physical robotic assembly cell

Advanced robotic assembly systems are promising great benefits to the manufacturing sector, once the shortcomings of the current technologies are overcome. One of the biggest obstacles to introducing flexible robotic systems is the ability of robots to sense and perceive the semi-structured or unstructured environment. This paper presents a cyber-physical system based framework of a robotic assembly cell that is capable of recognizing resources of assembly processes, based on information from various visual sensors and updating and adapting the assembly plan in the digital twin of the robotic cell. Thus, calculates and executes feasible motion plans of the robots based on accurate digital information. The application of the framework is demonstrated in a physical assembly process.

Rethinking the Power Delivery Networks of Mobile Robots

There are complex power system design and architecture considerations in the power delivery networks (PDN) of mobile robots, autonomous vehicles, and distributed static robots. This is due to the variation in the battery power source voltage plus the broad variety of loads that may be part of a typical system, such as, high-power AI computing systems, motor drives, sensors, communication systems, logic boards, and processors to name a few. Also, there are EMI considerations that naturally arise from developing closely-packed and dense systems that use high-power switching regulators. The result is that robotics power systems face many challenges that are unique to this set of applications, and therefore new approaches are needed to address them. This article explores how the performance and design flexibility of advanced robotic power systems can be enhanced by leveraging fixed-ratio power converters and high-efficiency wide-input-range buck or buck-boost regulators.

Minimally-invasive donor hepatectomy at the dawn of a decade: can we pick up the pace?

: Next year will mark two decades since the first minimally-invasive donor hepatectomy (MIDH) was performed in Paris to facilitate an adult-to-child live donor liver transplant (LDLT). Despite improvements and widespread proliferation of LDLT throughout the world, a concomitant broader application of the MIDH technique has not been wholly realized due to concerns over donor safety and the technical difficulties inherent to MIDH. On the contrary, during the same time period, minimally-invasive liver surgery (MILS) rapidly evolved into a standard approach for many benign and malignant forms of liver disease. To support this growth, numerous novel technologies such as advanced laparoscopy and robotic surgical systems, three-dimensional (3D) flexible videoscopy, real-time near-infrared fluorescence cholangiography with indocyanine green (ICG), and a variety of thermal energy devices and endovascular staplers have evolved and matured in the setting of MILS. A handful of select, high-volume liver transplant centers have incorporated these MILS advancements into their established segmental liver surgery and LDLT programs in order to develop the requisite technical sophistication to execute MIDH in an impactful manner. Two techniques, pure laparoscopic donor hepatectomy (PLDH) and robotic donor hepatectomy (DH), have emerged as the dominant modalities in MIDH surgery with each having their proponents and detractors. A few centers in Asia, France, the United States, and Saudi Arabia have recently reported series of sufficient volume and nuance to be instructive for the field in general. The intent of this review is to describe the experience to date in MIDH with a particular focus on lessons learned at these pioneering institutions who navigated through the learning curves in these demanding technical endeavors. The tricks, observations, and recommendations gleaned from this article should serve as a vital resource for those motivated surgeons embarking upon the challenging but rewarding field of MIDH surgery.

6-Axis Force/Torque Sensor With a Novel Autonomous Weight Compensating Capability for Robotic Applications

Force/Torque(F/T) sensing technology enables a dexterous robot control such as direct teaching, master-slave system, and pick-and-place task. In general, 6-axis F/T sensor is attached to the end-effector of the robot manipulator to assist in utilizing advanced robot systems. However, in actual applications, various tools such as robotic grippers, robotic hand, grinders are attached to the sensor and it causes F/T offsets with respect to the gravity. In this letter, Autonomous Weight Compensating(AWC) technique for 6-axis F/T sensor is presented. The proposed AWC technique can reduce the F/T offsets by estimating the F/T offsets through installed Inertial Measurement Unit(IMU) sensor. In this study, the 6-axis F/T are measured based on capacitance sensing scheme and to estimate the orientation of the sensor, a 9-axis IMU sensor is installed inside of the sensor. Then, the F/T offsets are calibrated via Artificial Neural Network(ANN) model. Finally, the performance of the proposed method is demonstrated through comparing the F/T data with both trained data and untrained data.

Automation and Robotics in Forest Harvesting Operations

Technology development, in terms of both capability and cost-effective integration, is moving at a fast pace. While advanced robotic systems are already commonplace in controlled workspaces such as factories, the use of remote controlled or autonomous machines in more complex environments, such as for forest operations, is in its infancy. There is little doubt autonomous machinery will play an important role in forest operations in the future. Many machine functions already have the support of automation, and the implementation of remote control of the machine where an operator can operate a piece of equipment, typically in clear line-of sight, at least is commonly available. Teleoperation is where the operator works from a virtual environment with live video and audio feedback from the machine. Since teleoperation provides a similar operator experience to working in the machine, it is relatively easy for an operator to use teleoperation. Autonomous systems are defined by being able to perform certain functions without direct control of a human operator. This paper presents opportunities for remote control, teleoperated machines in forest operations and presents examples of existing developments and ideas from both forestry and other industries. It identified the extraction phase of harvesting as the most logical placement of autonomous machines in the near-term. The authors recognise that, as with all emerging technologies and sectors, there is ample scope for differences in opinions as to what will be commercially successful in the future.

Radical Prostatectomy: from Open Surgery towards Robotic Laparoscopy

Radical prostatectomy was first performed more than 100 years ago and has since become the gold standard in treatment of localized prostate cancer. Open surgery has been almost entirely replaced by robotic operations referred to as robot-assisted radical prostatectomy (RARP). Th e article introduces the basics of this innovative standard of operative access and tackles medical and historical aspects, oncological, medical and economic management pros and contras of robotic aid over open radical prostatectomy. Surgical trauma in RARP is clearly less pronounced compared to open surgery due to a much earlier postoperative mobilisation and a faster rehabilitation of patients leading to a statistically significant reduction in the length of hospital stay after RARP. Along with advances in intracorporeal imaging with 16-fold optical magnification coupled with shorter urethral catheterisation, RARP facilitates an earlier start of pelvic floor exercises, which reduces postoperative incontinence and need for pain relievers. Th e already mentioned technical advantages of the robotic method hold value to both patient and surgeon by securing instant access for an experienced colleague without interrupting the surgery. Noteworthy, the increasing advancement of robotic systems across the globe is leading urologist surgeons to abandon open operations. A drawback of the robotic method is much higher economic costs. However, greater expenditures may pay off in the long run by shorter hospital stays, faster rehabilitation and fewer complications demanding extra management and care.

Speech recognition based robotic mart

In past many researchers have designed the multiple robots which served as per the need of humans but unfortunately they are much expensive. It has been observed that man power is needed in the shopping marts especially on highway based stores and marts. Where it is found to be inconvenient for persons or owners to perform the duties all the time. This paper is centered around one of the best solution in this regards that is the cheapest man–machine association by discourse where the robot can perceive the discourse and it can react to the individual in that instant. In this paper the prototype of a speech recognition based robotic mart has been designed and analyzed which is based on speech recognition system. To make it semi-autonomous it compares the data in database unit, if the data matches with any command within the database, it instructs to main system to perform that function accordingly. The proposed robotic mart is supposed to be an economical and advanced robotic system that consists of cheapest Arduino microcontroller as a main control unit and a smartphone based application software. Its GUI framework will help the user for addressing the gadget; it will carry the accommodation to the user discussing voice worked gadget controlling hence, decreases the human endeavors. User doesn't need to get up from his place to control the device and user can talk in mobile or some other gadgets utilizing the MIT application stage and afterward the directions are sent to the control unit through remote correspondence procedure by means of Bluetooth.

Polymer Optical Fiber-Based Integrated Instrumentation in a Robot-Assisted Rehabilitation Smart Environment: A Proof of Concept.

Advances in robotic systems for rehabilitation purposes have led to the development of specialized robot-assisted rehabilitation clinics. In addition, advantageous features of polymer optical fiber (POF) sensors such as light weight, multiplexing capabilities, electromagnetic field immunity and flexibility have resulted in the widespread use of POF sensors in many areas. Considering this background, this paper presents an integrated POF intensity variation-based sensor system for the instrumentation of different devices. We consider different scenarios for physical rehabilitation, resembling a clinic for robot-assisted rehabilitation. Thus, a multiplexing technique for POF intensity variation-based sensors was applied in which an orthosis for flexion/extension movement, a modular exoskeleton for gait assistance and a treadmill were instrumented with POF angle and force sensors, where all the sensors were integrated in the same POF system. In addition, wearable sensors for gait analysis and physiological parameter monitoring were also proposed and applied in gait exercises. The results show the feasibility of the sensors and methods proposed, where, after the characterization of each sensor, the system was implemented with three volunteers: one for the orthosis on the flexion/extension movements, one for the exoskeleton for gait assistance and the other for the free gait analysis using the proposed wearable POF sensors. To the authors’ best knowledge, this is the first time that optical fiber sensors have been used as a multiplexed and integrated solution for the simultaneous assessment of different robotic devices and rehabilitation protocols, where such an approach results in a compact, fully integrated and low-cost system, which can be readily employed in any clinical environment.

Focused section on advanced robotic systems for industrial automation

Focused section on advanced robotic systems for industrial automation

Position and Force Control of a Soft Pneumatic Actuator.

Recent advances in robotic systems have increased the need for various kinds of robots in many fields, such as aerospace and medical. Utilizing hard robots in such fields can cause irrecoverable damages; therefore, scientists have taken inspiration from nature to build robots with soft bodies. In this article, a soft pneumatic actuator that reshapes in the x-y plane is controlled. This continuous soft robot uses air pressure as actuation to control the end point position of the robot through curvature motion, and the force applied to a load cell. System identification approaches are used to model the behavior of the soft actuator, simulate time response, and design a suitable controller. After modeling the behavior of the actuator, a cascaded control strategy is used to control the robot. To increase precision in tracking control, using the Prandtl-Ishlinskii (P-I) method, existing hysteresis in the response of the system is measured, simulated, and then compensated using the inverse P-I method. The performance of the system, in the presence of the designed control architecture, is simulated and implemented on an experimental setup in the laboratory. Finally, tracking results are presented and compared for this soft actuator.