Robotic System Research Articles

High-speed odor sensing using miniaturized electronic nose.

Animals have evolved to rapidly detect and recognize brief and intermittent encounters with odor packages, exhibiting recognition capabilities within milliseconds. Artificial olfaction has faced challenges in achieving comparable results-existing solutions are either slow; or bulky, expensive, and power-intensive-limiting applicability in real-world scenarios for mobile robotics. Here, we introduce a miniaturized high-speed electronic nose, characterized by high-bandwidth sensor readouts, tightly controlled sensing parameters, and powerful algorithms. The system is evaluated on a high-fidelity odor delivery benchmark. We showcase successful classification of tens-of-millisecond odor pulses and demonstrate temporal pattern encoding of stimuli switching with up to 60 hertz. Those timescales are unprecedented in miniaturized low-power settings and demonstrably exceed the performance observed in mice. It is now possible to match the temporal resolution of animal olfaction in robotic systems. This will allow for addressing challenges in environmental and industrial monitoring, security, neuroscience, and beyond.

Efficiency and Heat Production of Ultrasonic Osteotome Strategy in Robot-Assisted Laminectomy.

A biomechanical study. We aimed to assess temperature fluctuations when applying the ultrasonic osteotome during laminectomy and identify the most appropriate cutting method for robot-assisted laminectomy to mitigate the risk of heat-related injuries. Utilizing a robotic system for laminectomy, the study implemented the ultrasonic bone scalpel to cut both artificial polyurethane bones and animal spinal bones. The research focused on comparing and analyzing the maximum temperature of the inner surface of four types of artificial bones through three different cutting techniques: vertical constant cutting at speeds of .5mm/s and 1mm/s, as well as robot-assisted vertical reciprocating cutting. After the initial results, two optimal vertical cutting approaches were selected for subsequent trials, evaluating the effectiveness and temperature impact of various ultrasonic osteotome modes on 10 isolated spinal bones from pigs. When cutting polyurethane bones, reciprocating cutting demonstrated the lowest maximum temperature in contrast to constant speed cutting at .5mm/s and 1mm/s. In the animal bone trial, direct cutting registered an average maximum temperature of 43.25°C with an average cutting duration of 688.3s, while reciprocating cutting recorded an average maximum temperature of 34.20°C with an average cutting time of 713.0s. The reciprocating cutting strategy utilized in robot-assisted ultrasonic osteotome is effective in reducing heat generation and maintaining high cutting efficiency.

Optical tweezer-assisted cell pairing and fusion for somatic cell nuclear transfer within an open microchannel.

Somatic cell nuclear transfer (SCNT), referred to as somatic cell cloning, is a pivotal biotechnological technique utilized across various applications. Although robotic SCNT is currently available, the subsequent oocyte electrical activation/reconstructed embryo electrofusion is still manually completed by skilled operators, presenting challenges in efficient manipulation due to the uncontrollable positioning of the reconstructed embryo. This study introduces a robotic SCNT-electrofusion system to enable high-precision batch SCNT cloning. The proposed system integrates optical tweezers and microfluidic technologies. An optical tweezer is employed to facilitate somatic cells in precisely reaching the fusion site, and a specific polydimethylsiloxane (PDMS) chip is designed to assist in positioning and pairing oocytes and somatic cells. Enhancement in the electric field distribution between two parallel electrodes by PDMS pillars significantly reduces the required external voltage for electrofusion/electrical activation. We employed porcine oocytes and porcine fetal fibroblasts for SCNT experiments. The experimental results show that 90.56% of oocytes successfully paired with somatic cells to form reconstructed embryos, 76.43% of the reconstructed embryos successfully fused, and 70.55% of these embryos underwent cleavage. It demonstrates that the present system achieves the robotic implementation of oocyte electrical activation/reconstructed embryo electrofusion. By leveraging the advantages of batch operations using microfluidics, it proposes an innovative robotic cloning procedure that scales embryo cloning.

Coordinated adaptive consensus tracking of multiple impacting oscillator robot systems via distributed interactions

Coordinated adaptive consensus tracking of multiple impacting oscillator robot systems via distributed interactions

Efficacy of domestic single-hole robotic surgery system in the treatment of pediatric urological diseases

To explore the efficacy of domestic single-hole robotic surgery system in the treatment of pediatric urological diseases. A prospective review of clinical data of children who underwent laparoscopic surgery in the Department of Urology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, was conducted from July to November 2023. All surgeries were performed using the sharp single-port serpentine arm robotic surgery system, with an umbilical access route. All surgeries are performed by the same chief physician. Operative time, intraoperative blood loss, incision size, and postoperative complications were recorded. A total of 12 patients were included, consisting of 8 males and 4 females, aged 8.0-17.0 (13.5±2.7) years. The procedures included 5 pyeloplasties (1 case of bilateral pyeloplasty), with a unilateral operative time [M (Q1, Q3) ]of 180 (145, 200) minutes and a blood loss of 5 (5, 10) ml. Oral mucosa ureteroplasty was performed in 1 patient, taking 3 hours and 52 minutes with a blood loss of 10 ml. Renal cyst decortication was conducted in 1 case in 85 minutes with a blood loss of 20 ml. High ligation of the spermatic vein was conducted in 3 patients, with an average operative time of 97 minutes and no intraoperative blood loss. Bilateral gonadectomy was completed in 80 minutes with a blood loss of 5 ml. Ovarian cystectomy (1 case) was performed in 69 minutes with a blood loss of 5 ml. All surgeries were successfully completed without conversion to open surgery. Except for the oral mucosa ureteroplasty, which required an additional 5 mm auxiliary port, all procedures were performed through a 3 cm umbilical incision. Among the patients who underwent pyeloplasty, 1 case of urinary leak was identified and successfully treated conservatively with adequate drainage over 25 days. Re-stenosis was experienced by 1 patient with a long segment ureteral stricture postoperatively, while no Clavien-Dindo grade≥2 complications were observed in other patients. All umbilical wounds were concealed, and satisfactory postoperative appearances were noted. The domestic single-hole robotic surgery system is effective in treating pediatric urological diseases.

Comprehensive Analysis of Major Fault-to-Failure Mechanisms in Harmonic Drives

The present paper proposes a detailed Failure Mode, Effects, and Criticality Analysis (FMECA) on harmonic drives, focusing on their integration within the UR5 cobot. While harmonic drives are crucial for precision and efficiency in robotic manipulators, they are also prone to several failure modes that may affect the overall reliability of a system. This work provides a comprehensive analysis intended as a benchmark for advancements in predictive maintenance and condition-based monitoring. The results not only offer insights into improving the operational lifespan of harmonic drives, but also provide guidance for engineers working with similar systems across various robotic platforms. Robotic systems have advanced significantly; however, maintaining their reliability is essential, especially in industrial applications where even minor faults can lead to costly downtimes. This article examines the impact of harmonic drive degradation on industrial robots, with a focus on collaborative robotic arms. Condition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) approaches are discussed, highlighting how digital twins and data-driven models can enhance fault detection. A case study using the UR5 collaborative robot illustrates the importance of fault diagnosis in harmonic drives. The analysis of fault-to-failure mechanisms, including wear, pitting, and crack propagation, shows how early detection strategies, such as vibration analysis and proactive maintenance approaches, can improve system reliability. The findings offer insights into failure mode identification, criticality analysis, and recommendations for improving fault tolerance in robotic systems.

Human-Centered Robotic System for Agricultural Applications: Design, Development, and Field Evaluation

This paper introduce advancements in agricultural robotics in response to the increasing demand for automation in agriculture. Our research aims to develop humancentered agricultural robotic systems designed to enhance efficiency, sustainability, and user experience across diverse farming environments. We focus on essential applications where human labor and experience significantly impact performance, addressing four primary robotic systems, i.e., harvesting robots, intelligent spraying robots, autonomous driving robots for greenhouse operations, and multirobot systems, as a method to expand functionality and improve performance. Each system is designed to operate in unstructured agricultural environments, adapting to specific needs. The harvesting robots address the laborintensive demands of crop collection, while intelligent spraying robots improve precision in pesticide application. Autonomous driving robots ensure reliable navigation within controlled environments, and multirobot systems enhance operational efficiency through optimized collaboration. Through these contributions, this study offers insights into the future of agricultural robotics, emphasizing the transformative potential of integrated, experience-driven intelligent solutions that complement and support human labor in digital agriculture.

Telesurgery: humanitarian and surgical benefits while navigating technologic and administrative challenges.

Telesurgery, the remote execution of surgical procedures through telecommunication and robotic systems, has witnessed substantial growth in recent years, promising to address global healthcare disparities and enhance surgical expertise. This paper explores the humanitarian and surgical benefits of telesurgery, emphasizing its potential to provide expert surgical care to underserved regions. Despite its transformative potential, telesurgery faces significant technologic challenges, including issues of data transmission, latency, and the need for advanced robotic platforms. The advent of 5G networks and innovative robotic systems provides a promising technological landscape, yet global disparities in 5G coverage remain a concern. Ethical considerations, ranging from preserving the surgeon-patient relationship to addressing patient vulnerability and conflicts of interest, are pivotal aspects that demand attention. The paper underscores the importance of clear regulatory frameworks and international collaboration to navigate legal complexities and ensure ethical standards. As telesurgery progresses, integrating artificial intelligence, augmented reality, and haptic feedback technologies holds promise for further advancements. Despite these challenges, telesurgery has the potential to achieve equitable access to expert surgical care; however, it requires a collective effort to overcome its intricate technologic and administrative hurdles.

Architectural views for social robots in public spaces: business, system, and security strategies

This study delineates a suite of architectural views and a security perspective tailored to guide the deployment and integration of Social Robots in Public Spaces (SRPS). It commences with a business context view that utilizes the customer-producer-supplier model, underscoring the value of SRPS to various stakeholders and illustrating how robots can enhance user experiences and drive economic benefits. The system context view details the intricate interactions among the social robot, stakeholders, public spaces, and external systems, highlighting essential considerations for successful deployment, from technical configurations to stakeholder engagement. The functional view elaborates on the operational dynamics of the robot within its environment, focusing on user interaction and data management capabilities. Additionally, the security perspective delves into security considerations vital for safeguarding the SRPS across various domains, including identity and access management, application and network security, and data privacy. The paper also contextualizes these views through a city ferry use case, demonstrating their practical application and reinforcing the importance of multifaceted planning and analysis in real-world settings. This approach provides a strategic framework views for developing SRPS that are viable, efficient, and secure, fostering successful adoption in diverse public environments.

Green Fruit‐Stem Pairing and Clustering for Machine Vision System in Robotic Thinning of Apples

ABSTRACTApples are one of the most highly‐valued specialty crops in the United States. Recent labor shortages have made crop production difficult for fruit growers, including the task of green fruit thinning. Current methods including hand, chemical, and mechanical thinning impose tradeoffs between selectivity, cost, tree damage, and speed. A robotic green fruit thinning system could potentially selectively thin fruit in a quick, cost‐effective, and non‐damaging manner. The machine vision system would be a critical component for robotic thinning, and would not only need to perform green fruit detection/segmentation, but also fruit‐stem pairing and clustering to facilitate proper decision‐making for thinning. A neural network‐based fruit and stem pairing algorithm was devised and evaluated; an LSTM‐based clustering algorithm was devised and compared to the density‐based clustering algorithm, OPTICS. The algorithms were evaluated on an image data set consisting of GoldRush, Fuji, and Golden Delicious cultivars at the green fruit stage, with evaluations on overall performance, cultivar‐wise performance, cluster size‐specific performance, and feature importance. For fruit and stem pairing, the neural network‐based pairing algorithm achieved an AP of 81.4% on all fruits and stems, and that reached 90.6% when only fruits and stems with labeled angles were considered. For green fruit clustering, the LSTM‐based clustering achieved a clustering success rate of 68.4%, whereas the OPTICS algorithm obtained 50.9%. The algorithms will be further implemented in a pipeline of a future green fruit thinning vision system, as well as integrate the use of point clouds and other 3D orchard information to improve pairing and clustering performance.

Survey of learning-based approaches for robotic in-hand manipulation

Human dexterity is an invaluable capability for precise manipulation of objects in complex tasks. The capability of robots to similarly grasp and perform in-hand manipulation of objects is critical for their use in the ever changing human environment, and for their ability to replace manpower. In recent decades, significant effort has been put in order to enable in-hand manipulation capabilities to robotic systems. Initial robotic manipulators followed carefully programmed paths, while later attempts provided a solution based on analytical modeling of motion and contact. However, these have failed to provide practical solutions due to inability to cope with complex environments and uncertainties. Therefore, the effort has shifted to learning-based approaches where data is collected from the real world or through a simulation, during repeated attempts to complete various tasks. The vast majority of learning approaches focused on learning data-based models that describe the system to some extent or Reinforcement Learning (RL). RL, in particular, has seen growing interest due to the remarkable ability to generate solutions to problems with minimal human guidance. In this survey paper, we track the developments of learning approaches for in-hand manipulations and, explore the challenges and opportunities. This survey is designed both as an introduction for novices in the field with a glossary of terms as well as a guide of novel advances for advanced practitioners.

Evolutionary robotics as a modelling tool in evolutionary biology

The use of evolutionary robotic systems to model aspects of evolutionary biology is well-established. Yet, few studies have asked the question, “What kind of model is an evolutionary robotic system?” This paper seeks to address that question in several ways. First, it is addressed by applying a structured model description developed for physical robot models of animal sensorimotor systems, then by outlining the strengths and limitations of evolutionary robotics for modelling evolutionary biology, and, finally, by considering the deepest questions in evolution and which of them might feasibly be modelled by evolutionary robotics. The paper concludes that although evolutionary robotics faces serious limitations in exploring deeper questions in evolutionary biology, its bottom-up approach to modelling populations of evolving phenotypes and their embodied interactions holds significant value for both testing and generating hypotheses.

Challenges in service robot devices for elderly motion assistance

Abstract Motion assistance for elderly people is a field of application for service robotic systems that can be characterized by requirements and constraints of human–machine interaction and by the specificity of the user’s conditions. The main aspects of characterization and constraints are examined for the application of service systems that can be specifically conceived or adapted for elderly motion assistance by having to consider conditions of motion deficiency and muscular strength weakness as well as psychological aptitudes of users. The analysis is discussed in general terms with reference to elderly people who may not even suffer from specific pathologies. Therefore, the discussion focuses on the need for motion exercise in proper environments, including domestic ones and frame familiar to a user. The challenges of such applications oriented toward elderly users are discussed as requiring research and design of solutions in terms of specific portability, user-oriented operation, low costs, and clinical-physiotherapeutic functionality. Results of the author’s team experiences are presented as an example of problems and attempted solutions to meet the new challenges of service systems for motion assistance applications for elderly people.

Complete Visibility Algorithms of Luminous Robots With Two‐Color Lights on Grid

ABSTRACTAn autonomous mobile robot system is a distributed system consisting of multiple mobile computational entities, called robots, which autonomously and repeatedly perform three fundamental operations: look, compute, and move. Various challenges in such systems, including gathering, pattern formation, and flocking, have been extensively studied to explore the relationship between the robots' capabilities and the feasibility of solving these problems (i.e., solvability). In this study, we focus on the complete visibility problem, which aims to relocate all robots on an infinite grid plane so that every robot is visible to every other robot (i.e., complete visibility). We assume that each robot is a luminous robot (i.e., has a light with a constant number of colors) and opaque (non‐transparent). This paper primarily examines the number of light colors required for each robot to solve the complete visibility problem. Specifically, we investigate the question: “how many colors can we reduce while still achieving complete visibility?” (even under certain stronger assumptions). As an answer to the above question, we show the existence of a deterministic algorithm to achieve complete visibility (i.e., every robot can observe all the other robots) using only two colors of light, if the robots agree on the directions and orientations of both axes. The proposed algorithm correctly works even if robots operate asynchronously and have no knowledge of the total number of robots. Moreover, its spatial complexity (i.e., the area of the smallest enclosed rectangle that includes all robots in the final configuration) ensures the optimal one, , where is the number of robots.

Impulsive tracking synchronization control of networked robotic manipulator systems in the task space

This study investigates the impulsive tracking synchronization control of networked robotic manipulator systems based on Lagrangian systems. In the task space, the end-effector positions of networked robotic manipulators can synchronize and track a desired trajectory by designing an impulsive controller. Based on impulsive control, some algebraic synchronization criteria are derived. As a direct application of the theoretical results, tracking synchronization of six double-link robotic manipulators in the task space is discussed in detail. Numerical simulations are given to demonstrate the effectiveness and feasibility of the proposed control strategy.

Development of a Load‐Bearing, Terrain‐Adaptive Hexapod Robot With Chebyshev‐Linkage Legs

ABSTRACTThis study introduces an exploratory design for a hexapod load‐carrying robot, aiming to address challenges commonly associated with quadruped robots, including limited load capacity and high control complexity. By leveraging a Chebyshev linkage‐based overconstrained leg‐foot architecture that combines high rigidity and low friction, along with a multi‐drive system for lateral movement, we propose a robot with improved adaptability to diverse terrains, such as snow, sand, puddles, ice, and deserts. This versatility suggests potential applications in areas such as factory inspection, field reconnaissance and transport, and desert exploration. Using static and dynamic analyses, we evaluated the leg structure's stress distribution and motion requirements, employing simulations in Workbench and Adams to cross‐validate our theoretical calculations. The development of a prototype and its subsequent testing under various environmental conditions aimed to demonstrate the design's practicality and the robot's operational capabilities in real‐world settings. Although the findings indicate progress toward enhancing load‐bearing capabilities and terrain adaptability with reduced control complexity, further research and development are necessary to fully realize the potential of such robotic systems in practical applications.

Artificial Intelligences in Industrial Robots: A Framework Based on Gardner’s Multiple Intelligences

Industrial robots, both in manufacturing and non-manufacturing sectors, are evolving rapidly, driven by advancements in artificial intelligence (AI). This paper presents a comprehensive survey of industrial robots, framed through the lens of Howard Gardner’s theory of multiple intelligences. By categorising various AI capabilities in industrial robots—such as visual recognition, decision-making, and collaborative interaction—based on Gardner’s intelligence framework, we provide a novel taxonomy that bridges human cognitive abilities and artificial systems. The survey explores the historical development of industrial robots, the current state of AI implementation, and future trends in robotics. Additionally, we discuss the implications of these advancements for industries and their workforce, as well as the ethical considerations surrounding the growing autonomy of AI systems. This paper aims to serve as a reference point for researchers and professionals seeking to understand the intersection of cognitive science and industrial AI, highlighting the potential and challenges of integrating AI into robotic systems.

A FMEA Optimization Method Based on TODIM and Best Worst Method-Water Filling Theory in Pythagorean Fuzzy Language Environment for Reliability Assessment of Industrial Robot

Abstract In view of the shortcomings of traditional failure modes and effects analysis (FMEA) in risk evaluation language, weight information, risk priority number (RPN), this paper proposes an FMEA optimization method. First, using the Pythagorean fuzzy language as the evaluation language, the hesitation psychology of the evaluator is truly reflected. Then, the best worst method (BWM) is used to calculate the weight of the evaluator, it can reduce the number of pairwise comparison evaluations. Second, water filling theory (WFT) uses mean values instead of extreme values to determine the discreteness of evaluation information, which is more consistent with FMEA. Therefore, WFT is used to calculate the weight of influencing factors. Finally, the tomada de-decisao iterativa multicriterio (TODIM) method is used for compromise calculation to obtain the risk ranking of failure modes. Compared with RPN, TODIM can avoid the situation that the failure mode scores are the same. At the end of the paper, the robustness and superiority of the new method are verified by taking the reliability assessment of reversing system of industrial robots as an example.

A Fast Chebyshev Collocation Method for Stability Analysis of a Robotic Machining System with Time Delay

A Fast Chebyshev Collocation Method for Stability Analysis of a Robotic Machining System with Time Delay

Design and realization of an isomorphic master-slave robotic system for precise sub-micrometer manipulations in ophthalmic surgery

Design and realization of an isomorphic master-slave robotic system for precise sub-micrometer manipulations in ophthalmic surgery