Robot Software Research Articles

Software supported robotic PCI in coronary arteries – comparison from the ROBO.pci trial

Abstract Background Robotic percutaneous coronary interventions (rPCI) have proven to be efficient and safe. The robotics software has recently been updated and now allows precise and fully controlled navigation of devices and wires to fit the various morphologic conditions of coronary arteries and calcified segments. Objectives In the present study we aimed to compare the different robotic wiring modalities supported by the new software. Study design rPCI performed using the updated robotics software was compared with rPCI using the manually executed wire positioning. Lesion crossing was performed with each method under identical circumstances, crossing the same lesion and measuring the wire times. Measurements were started at the ostium of the guiding catheter and were stopped at a pre-defined individual coronary anatomical landmark. Results Eleven consecutive patients with 11 lesions were enrolled in this trial. The mean age of patients was 63±6 years with typical cardiovascular comorbidities and 54% (6/11) presented with three-vessel disease. All patients underwent PCI in an elective setting with stable chronic coronary syndrome. The majority of lesions were located in the LCX (45%, 5/11) followed by the LAD (27%, 3/11) and the RCA (27%, 3/11). All lesions were de novo ACC/AHA grade B2/C lesions, and the procedure was performed by experienced (high-volume) interventional cardiologists. The lesion crossing times were not significantly different (manual crossing 15.00 [IQR: 40] sec vs. rPCI without software support 18.00 [IQR: 18] sec vs. rPCI with software support 13.00 [IQR: 47] sec; p=n.s.). Summary rPCI without software support tends to be slower than rPCI with software support. There was no statistical significance. rPCI was found to be safe and feasible and the new software tends to reduced procedural time, which could reduce operators' health risks and improve patients' outcomes. Further randomized controlled trials are needed to evaluate the long-term benefits. Funding Acknowledgement Type of funding sources: None.

Gaining and Training a Digital Colleague: Employee Responses to Robotization

This study shows how introducing new technology can be like welcoming a digital colleague. Designed to mimic the actions of employees, robotic process automation is a technology that involves developing software robots to perform standardized tasks. Although beneficial for the firm, robotization may come at a cost for the employees, since the technology puts positions at risk by automating manual procedures. In this study, I used a case study approach to examine how employees responded to robotization in three organizations. The findings revealed that the employee responses were overwhelmingly constructive and positive. In addition to responding with a big-picture perspective and finding opportunities, the employees humanized software robots as new digital colleagues, with whom they developed relationships. The results discussed in this study contribute to understanding technology-driven change by empirically illustrating employees’ multidimensional—affective, behavioral, and cognitive—responses to robotization, and the supportive context securing implementation.

Quagents: A Game Platform for Intelligent Agent

The Quagents system provides a flexible interface to the functionality of a game engine. The goal is to make interactive games a useful research and teaching vehicle for academics. Quagents is freely available, and runs under Unix/Linux, Windows, and Mac OS X. Intelligent agent controllers may be programmed in any language that supports sockets. A communications protocol between the controller and the bot resembles that between the high-level software and low-level controller of a mobile robot. More complex APIs may be built on the protocol that support complex interactions like trading. We describe the Quagent architecture and research and teaching applications.

Hybrid Intelligence: to automate or not to automate, that is the question

There used to be a clear separation between tasks done by machines and tasks done by people. Applications of machine learning in speech recognition (e.g., Alexa and Siri), image recognition, automated translation, autonomous driving, and medical diagnosis, have blurred the classical divide between human tasks and machine tasks. Although current Artificial Intelligence (AI) and Machine Learning (ML) technologies outperform humans in many areas, tasks requiring common sense, contextual knowledge, creativity, adaptivity, and empathy are still best performed by humans. Hybrid Intelligence (HI) blends human intelligence and machine intelligence to combine the best of both worlds. Hence, current and future Business Process Management (BPM) initiatives need to consider HI and the changing boundaries between work done by people and work done by software robots. Consider, for example, the success of Robotic Process Automation (RPA), which demonstrates that gradually taking away repetitive tasks from workers is possible. In this viewpoint paper, we argue that process mining is a key technology to decide what to automate and what not. Moreover, using process mining, it is possible to systematically monitor and manage processes where work is distributed over human workers and software robots.

I-fiber implantation robot for composite parts

I-fiber implantation is a new stitching technology that can effectively enhance the interlayer performance of laminated composites. This paper presents and evaluates the design and implementation of the I-fiber robot implantation system integrated for producing high-performance fiber preforms for advanced composites. The system was constructed and validated through I-fiber robot implantation experimentation. It was demonstrated that automated I-fiber implantation could be achieved by use of an industrial robot. The programming method and computer-aided manufacturing software of the I-fiber implantation robot were feasible and effective. The double-cantilever-beam (DCB) experiments showed that the implantation of I-fiber significantly improved the interlaminar fracture toughness of the laminated composite, where the maximum load value increased by up to 106%. The DCB load–displacement curve presented a zigzag shape, where the peaks and valleys were the location points of the I-fiber break. It was also found that for the reinforced laminated composite without an I-fiber head, the delamination failure was manifested as resin cracking and I-fiber pullout, while for the I-fiber with a certain head length, the I-fiber failure mechanism was brittle fracture. I-fiber with a certain head length could significantly improve the interlayer performance of the composite. In addition, DCB experiments also revealed that the implantation matrix had little effect on the interlayer performance of I-fiber reinforced composites, and the failure load value and the I-fiber implantation volume showed an obvious proportional relationship.

Motion Capture and Intelligent Correction Method of Badminton Movement Based on Machine Vision

In recent years, badminton has become more and more popular in national fitness programs. Amateur badminton clubs have been established all over the country, and amateur badminton events at all levels have increased significantly. Due to the lack of correct medical supervision and health guidance, many people have varying degrees of injury during sports. Therefore, it is very important to study the method of badminton movement capture and intelligent correction based on machine vision to provide safe and effective exercise plan for amateur badminton enthusiasts. This article aims to study the methods of motion capture and intelligent correction of badminton. Aiming at the shortcoming of the mean shift algorithm that it is easy to lose the target when the target is occluded or the background is disturbed, this paper combines the mean shift algorithm with the Kalman filter algorithm and proposes an improvement to the combined algorithm. The improved algorithm is added to the calculation of the average speed of the target, which can be used as the target speed when the target is occluded to predict the area where the target may appear at the next moment, and it can also be used as a judgment condition for whether the target is interfered by the background. The improved algorithm combines the macroscopic motion information of the target, can overcome the problem of target loss when the target is occluded and background interference, and improves the robustness of target tracking. Using LabVIEW development environment to write the system software of the Japanese standard tracking robot, the experiment verified the rationality and correctness of the improved target tracking algorithm and motion control method, which can meet the real-time performance of moving target tracking. Experimental results show that 83% of amateur badminton players have problems with asymmetric functions and weak links. Based on machine vision technology, it can provide reliable bottom line reference for making training plans, effectively improve the quality of action, improve the efficiency of action, and promote the development of sports competitive level.

The Adoption of Robotic Process Automation Technology to Ensure Business Processes during the COVID-19 Pandemic

The study provides knowledge on the adoption of the Robotic Process Automation (RPA) technology during the COVID-19 pandemic in 110 Polish service companies. As this research was the first of its kind in Poland, the objectives of the CAWI survey were to identify the technology features of the RPA technology and the related determinants and barriers influencing the adoption of the RPA as well as to determine correlations between them. Moreover, the statistical analyses involved considering whether there were differences in the evaluation of individual RPA technology features, mainly in terms of perceived usefulness, ease of use, security and functionality. The results of the study show that almost 60% of the respondents indicated that robotization tools allowed maintaining continuity of business processes during the pandemic. The highest rated were features related to usefulness of the RPA technology. Furthermore, the analysis pointed to the most frequently indicated barriers to technology implementation that were related to nonoptimized, nonstandardized and non-digitized processes with a large number of exceptions. The study contributes to scientific knowledge and has practical implications for process automation decision-makers concerned with the adoption of the Robotic Process Automation technology. The obtained results can help them to understand the potential drivers of and barriers to the adoption of software robots by enterprises and may be an important determinant for companies’ managers in the field of implementing such solutions.

True Kinematic Alignment Is Applicable in 44% of Patients Applying Restrictive Indication Criteria-A Retrospective Analysis of 111 TKA Using Robotic Assistance.

Introduction: Image-based robotic assistance appears to be a promising tool for individualizing alignment in total knee arthroplasty (TKA). The patient-specific model of the knee enables a preoperative 3D planning of component position. Adjustments to the individual soft-tissue situation can be done intraoperatively. Based on this, we have established a standardized workflow to implement the idea of kinematic alignment (KA) for robotic-assisted TKA. In addition, we have defined limits for its use. If these limits are reached, we switch to a restricted KA (rKA). The aim of the study was to evaluate (1) in what percentage of patients a true KA or an rKA is applicable, (2) whether there were differences regarding knee phenotypes, and (3) what the differences of philosophies in terms of component position, joint stability, and early patient outcome were. Methods: The study included a retrospective analysis of 111 robotic-assisted primary TKAs. Based on preoperative long leg standing radiographs, the patients were categorized into a varus, valgus, or neutral subgroup. Initially, all patients were planned for KA TKA. When the defined safe zone had been exceeded, adjustments to an rKA were made. Intraoperatively, the alignment of the components and joint gaps were recorded by robotic software. Results and conclusion: With our indication for TKA and the defined boundaries, “only” 44% of the patients were suitable for a true KA with no adjustments or soft tissue releases. In the varus group, it was about 70%, whereas it was 0% in the valgus group and 25% in the neutral alignment group. Thus, significant differences with regard to knee morphotypes were evident. In the KA group, a more physiological knee balance reconstructing the trapezoidal flexion gap (+2 mm on average laterally) was seen as well as a closer reconstruction of the surface anatomy and joint line in all dimensions compared to rKA. This resulted in a higher improvement in the collected outcome scores in favor of KA in the very early postoperative phase.

Self-Organised Collision-Free Flocking Mechanism in Heterogeneous Robot Swarms

Flocking is a social animals’ common behaviour observed in nature. It has a great potential for real-world applications such as exploration in agri-robotics using low-cost robotic solutions. In this paper, an extended model of a self-organised flocking mechanism using heterogeneous swarm system is proposed. The proposed model for swarm robotic systems is a combination of a collective motion mechanism with obstacle avoidance functions, which ensures a collision-free flocking trajectory for the followers. An optimal control model for the leader is also developed to steer the swarm to a desired goal location. Compared to the conventional methods, by using the proposed model, the swarm network has less requirement for power and storage. The feasibility of the proposed self-organised flocking algorithm is validated by realistic robotic simulation software.

Autonomous underwater vehicle challenge: design and construction of a medium-sized, AI-enabled low-cost prototype

The design of an autonomous underwater vehicle (AUV) with physical dimensions of 1100 mm × 700 mm × 330 mm, and weight of 55 kg, is introduced herein. This paper describes the design, materials, hydrodynamics, and system architecture of an AUV prototype named Synoris, developed as a low-cost and medium-scale testbed platform. Synoris moves via six brushless motors, can reach up to 200 m depth, has an autonomy estimated around 6 hours and a modular design for multiple payload options. Stability control, autonomous movement, obstacle avoidance temperature/pressure sensing, and video/image capturing are simultaneously performed by exploiting a set of onboard computers that are described briefly in Section 4. The whole platform is built on top of the open source software called ROS (robotic operating system) that provides a flexible framework for writing robot software by providing services such as low-level device control, message parsing, data fusion, and system integration. Synoris is ideal for underwater applications and missions, involving machine learning and computer vision features. AUV development in general meets high-cost solutions due to the complexity and harshness of the operational environment. Even the most cost-effective solutions demand plentiful resources. This paper describes the entire process of development and how a relatively low-cost approach can provide a reliable AUV for many underwater applications, involving AI and machine-learning capabilities.

Is laparoscopic experience helpful in simulator based robotic training in general surgery?

To evaluate whether or not prior laparoscopic training improves performance during robotic surgery utilising DaVinci robotic skills simulator. The cross-sectional study was conducted at the Civil Hospital, Karachi, from May 4 to November 11, 2018, and comprised first year residents in Group A with no laparoscopic skills and fourth year residents doing laparoscopic cholecystectomy independently and surgical faculty members in Group B who had laparoscopic skills. Both the groups had no previous exposure to robotic surgery and skills simulator. There were 4 exercises which were repeated three times by each participant. Scoring was done using the DaVinci robotic skills simulator software. Data was analysed using SPSS 22. Of the 30 surgeons, there were 15(50%) in Group A with a mean age of 26±0.56 years, and 15(50%) in Group B with a mean age of 32 ± 9.16 Years (p<0.001). The overall mean age was 32±9.16 years (range: 25-52 years). There were 19(63.3) females in the sample compared to 11(36.6%) males. Mean scores of Ring walk 2, Peg board 2, and Suture sponge 3 were better in Group A, while mean score of Matchboard 2 was better in Group although B (p>0.05). Group B fared better in the individual scoring of Suture sponge 2 (p>0.05). Laparoscopic skills apparently did not confer any benefit while performing exercises on the DaVinci skills simulator.

On the Implementation of Behavior Trees in Robotics

There is a growing interest in Behavior Trees (BTs) as a tool to describe and implement robot behaviors. BTs were devised in the video game industry and their adoption in robotics resulted in the development of ad-hoc libraries to design and execute BTs that fit complex robotics software architectures. While there is broad consensus on how BTs work, some characteristics rely on the implementation choices done in the specific software library used. In this letter, we outline practical aspects in the adoption of BTs and the solutions devised by the robotics community to fully exploit the advantages of BTs in real robots. We also overview the solutions proposed in open-source libraries used in robotics, we show how BTs fit in robotic software architecture, and we present a use case example.

Software and control shell for service robots with parallel computing

KIAM Russian Academy of Sciences, International Laboratory «Sensorika» conduct research and development of service robots for tasks of telemedicine. The developed mobile robot AMUR-307 is planned to be used in clinics to move various objects between the premises of the building, separated by thresholds, stairs and doors. The robot is controlled remotely via a radio channel from the operator's post. It is also intended to minimize operator interference and apply the developed algorithms for autonomous operation using an on-board computing device. To control robots of this type, a software and hardware microprocessor system was designed and manufactured and its comprehensive testing was performed. The solution allows you quickly make changes to the customer's requirements and deliver robots, integrating them into the existing infrastructure. The article presents the results of research and comparison of various ways to implement the robot, optimize its structure, replication technology and parallel programming using the GPU.

Implementation of the visual data processing algorithms for onboard computing units

According to the short analysis of modern experience of hardware and software for autonomous mobile robots a role of computer vision systems in the structure of those robots is considered. A number of configurations of onboard computers and implementation of algorithms for visual data capturing and processing are described. In original configuration space the «algorithms-hardware» plane is considered. For software designing the realtime vision system framework is used. Experiments with the computing module based on the Intel/Altera Cyclone IV FPGA (implementation of the histogram computation algorithm and the Canny's algorithm), with the computing module based on the Xilinx FPGA (implementation of a sparse and dense optical flow algorithms) are described. Also implementation of algorithm of graph segmentation of grayscale images is considered and analyzed. Results of the first experiments are presented.

E-Commerce product comparison portal for classification of customer data based on data mining

In this search paper scrapping the data such as product name, product price, product reviews and ratings related to suggested products from Flipkart and Amazon using Robotic Process Automation tool and data is cleaned in order to remove noisy values and based on the user request the products from Flipkart and Amazon is suggested on E-Commerce portal based on user preferences the user can purchase the product from any site which is completely dependent on user. The RPA tool i.e., UiPath is used to create software robot for both Flipkart and Amazon, this bot is used to scrape the data from Flipkart and Amazon and perform cleaning operation and dump the data to database which can be used for future use. And the bot can be triggered on daily basis for data collection for database updation. This E-Commerce portal helps to categorize and distinguish the product purchase behavior and satisfy the end customer requirements.

Pulling Data from Multiple Websites to Identify Best Deals on Auction Websites

Robotic process automation(RPA)is an emerging tool of automation technology based on notion of software robots or Artificial intelligence(AI). If the customer wants to buy a Bluetooth speaker. He will go to flip kart and search the product. and see the prices as expensive. He will buy it .But the same product is cheaper in Amazon. So our project will give the best product based on the best price and best rating.

PIN Inference Attack: A Threat to Mobile Security and Smartphone-Controlled Robots

The proliferation of smartphones equipped with various sensors created a large user base, which includes robots (smartphone controlled) as well. The high processor enabled smartphones are used as software robots to track hour-to-hour activities of users using on-board motion sensors. The magnetometer, accelerometer, and gyroscope are non-permission based motion sensors. The logs of these sensors create discriminative patterns to identify users’ movements. This leverages an adversary to cause privacy threats using these non-permission based sensors without user consent. Recent works also highlighted the privacy threats due to the motion sensors in smartphones. Therefore, in this paper, we present a potential misuse of technology where smartphones can be hacked by PIN Inference attack endangering the mobile security. Once the smartphone is compromised, it may lead to various repercussions. We discuss one such case where after PIN is inferred the adversary incorrectly uses our robot made for corridor detection. With this example, we show the severity of the PIN-Inference attack as nowadays many user activities are governed by robots. We perform experiments to collect motion sensors’ data and infer 4-digit PIN of a smartphone. Our strategy is to detect every key pressed one by one constituting a 4-digit PIN. Our inference results are promising and prove that an adversary can make use of sensors’ data to infiltrate user’s sensitive information from smartphones. Our proposed model infers 84% of the PINs correctly within 40 attempts when tested on 50 PINs. Given real Android devices with different users, we can identify the PIN of smartphones by training our machine learning based model. We also compare our approach with existing state-of-the-art approaches to show the efficacy of our attack model.

Mining guidelines for architecting robotics software

Context:The Robot Operating System (ROS) is the de-facto standard for robotics software. However, ROS-based systems are getting larger and more complex and could benefit from good software architecture practices. Goal:We aim at (i) unveiling the state-of-the-practice in terms of targeted quality attributes and architecture documentation in ROS-based systems, and (ii) providing empirically-grounded guidance to roboticists about how to properly architect ROS-based systems. Methods:We designed and conducted an observational study where we (i) built a dataset of 335 GitHub repositories containing real open-source ROS-based systems, and (ii) mined the repositories to extract and synthesize quantitative and qualitative findings about how roboticists are architecting ROS-based systems. Results:First, we extracted an empirically-grounded overview of the state of the practice for architecting and documenting ROS-based systems. Second, we synthesized a catalog of 47 architecting guidelines for ROS-based systems. Third, the extracted guidelines were validated by 119 roboticists working on real-world open-source ROS-based systems. Conclusion:Roboticists can use our architecting guidelines for applying good design principles to develop robots that meet quality requirements, and researchers can use our results as evidence-based indications about how real-world ROS systems are architected today, thus inspiring future research contributions.

Rosy: An elegant language to teach the pure reactive nature of robot programming

Robotics is very appealing and is long recognized as a great way to teach programming, while drawing inspiring connections to other branches of engineering and science such as maths, physics or electronics. Although this symbiotic relationship between robotics and programming is perceived as largely beneficial, educational approaches often feel the need to hide the underlying complexity of the robotic system, but as a result fail to transmit the reactive essence of robot programming to the roboticists and programmers of the future. This paper presents Rosy, a novel language for teaching novice programmers through robotics. Its functional style is both familiar with a high-school algebra background and a materialization of the inherent reactive nature of robotic programming. Working at a higher-level of abstraction also teaches valuable design principles of decomposition of robotics software into collections of interacting controllers. Despite its simplicity, Rosy is completely valid Haskell code compatible with the ROS~ecosystem. We make a convincing case for our language by demonstrating how non-trivial applications can be expressed with ease and clarity, exposing its sound functional programming foundations, and developing a web-enabled robot programming environment.

Bootstrapping MDE development from ROS manual code: Part 2\u2014Model generation and leveraging models at runtime

Model-driven engineering (MDE) addresses central aspects of robotics software development. MDE could enable domain experts to leverage the expressiveness of models, while implementation details on different hardware platforms would be handled by automatic code generation. Today, despite strong MDE efforts in the robotics research community, most evidence points to manual code development being the norm. A possible reason for MDE not being accepted by robot software developers could be the wide range of applications and target platforms, which make all-encompassing MDE IDEs hard to develop and maintain. Therefore, we chose to leverage a large corpus of open-source software widely adopted by the robotics community to extract common structures and gain insight on how and where MDE can support the developers to work more efficiently. We pursue modeling as a complement, rather than imposing MDE as separate solution. Our previous work introduced metamodels to describe components, their interactions, and their resulting composition. In this paper, we present two methods based on metamodels for automated generation of models from manually written artifacts: (1) through static code analysis and (2) by monitoring the execution of a running system. For both methods, we present tools that leverage the potentials of our contributions, with a special focus on their application at runtime to observe and diagnose a real system during its execution. A comprehensive example is provided as a walk-through for robotics software practitioners.