Robotic Platform Research Articles

Development of an IoT based 3D printed Mobile Robot Platform for training of Mechatronics Engineering Students

The advent of the Internet of Things (IoT) has opened up new opportunities in education, particularly in the field of mobile robotics. Mobile robotics is a fast-growing field, and with the increasing demand for skilled robotics engineers, it is essential to provide students with hands-on experience in designing and developing robots. In this regard, an IoT-based 3D printed mobile robot platform has been developed for students training. STEM (Science, Technology, Engineering, and Mathematics) education has been gaining attention as a means to improve science and engineering education. STEM education aims to foster critical thinking, problem-solving skills, creativity, and innovation among students. It involves an educational policy that aims to develop the next generation of skilled professionals by integrating the fields of Science, Technology, Engineering and Mathematics. The goal of this approach is to provide students in mechatronics, who are assigned to the robotics lab during their studies, an up to date knowledge and experience in research and development activities. Thus, this paper aims to provide education that focuses on the acquisition and application of engineering knowledge, including control engineering, mechanical engineering, electrical and electronic engineering, information engineering, among others, with the main focus on mobile robot research.

Enhancing accuracy in field mobile robot state estimation with GNSS and encoders

The enhancement of accuracy remains a significant concern in state estimation for field mobile robots. This paper introduces a novel sensor fusion method to refine the accuracy of state estimation, employing global navigation satellite systems (GNSS) and encoders. This technique integrates a nonlinear observer for estimating the state of nonlinear systems and an unscented Kalman filter (UKF) to ascertain the robot’s state variables using signals from GNSS and encoder-based position sensors. In the proposed method, the nonlinear observer updates sigma points through nonlinear transformation and the UKF optimizes state estimation. Parameters are optimized through the particle swarm optimization method with the objective of minimizing the root mean square error of the state. To demonstrate performance, numerical simulations compare the proposed method with well-known nonlinear estimation algorithms, illustrating its effectiveness in field mobile robot state estimation. The method is further validated through implementation on a real-world mobile robot platform.

New Endoluminal platforms and advancements in technology: Should Gastroenterologists or Surgeons pave the way?

Nowadays, endoscopy has achieved amazing results in the treatment of benign and malignant pathologies, but it has yet to establish itself fully in the sense of an operative endoscopy. It is commonly believed that traditional endoscopy has reached its limits due to the intrinsic characteristics of existing platforms. Numerous robotic endoluminal platforms have been developed to overcome limitations in recent years. Existing robotic endoluminal platforms can be divided into three categories: fully robotic flexible endoscopic, robotic add-on systems, and traditional surgery-based platforms. These platforms are incredible pieces of technology, but in reality, they can only be considered a bridge to a genuinely robotic surgical system. Nowadays, both gastroenterologists and surgeons perform endoscopic procedures all over the world. We believe these platforms, leading to increased manipulation possibilities, may require an increasingly excellent knowledge of surgical techniques to develop their potential fully. Surgeons' unique training and experience push surgeons to take the lead in endoscopic operations over gastroenterologists due to the potential advantages in surgical precision and patient outcomes. However, gastroenterologists deeply understand gastrointestinal disorders and a collaborative effort between them and surgeons can lead to an efficient approach to endoscopic surgery.

Moving to Advanced Research on Human Machine Interface Design

This poster paper will discuss a variety of items related to Human-Machine Teaming and research in support in-creasing control of autonomous machines present in phys-ical problem domains of interest. Many military tasks can be decomposed into their primary elements – intelligence preparation, reconnaissance, movement, maneuver, fires, and and support across the combat domains of interest – air, land, sea, etc. There are an increasing number of au-tonomous and semi-autonomous ground-based systems available, such as the Multi-Utility Tactical Transport (MUTT) Unmanned Ground Vehicle, for movement of materials, or Quadrupedal Unmanned Ground Vehicle (QUGV) for the disposal of explosive ordinance, comple-mented by aerial platforms considering of a wide variety of Unmanned Aerial Systems (UAS) for the gathering and transmitting of information, held together by a common backbone and network. The preponderance of new systems and capabilities brings new issues, one of which is critical to research - how to control and manage a large number of systems. Commercial systems of significantly less capability, such as light-up drone shows, involve approximately 2 people per 100 drones; meaning that a single controller for a sin-gle drone is simply a non-starter. How can research be applied to scale the complexity of operations upwards without additional demands of personnel? This poster discusses several portions of early-stage research into a variety of applications, including: Reasoning about mixed-team processes, includ-ing real/synthetic teammates, and how infor-mation gathered about the use of synthetic teammates within simulation can be transitioned into utilization for a robotic teammate Embedding affective information into dialogue channels in order to save cognitive bandwidth Repurposing of foundational dialogue models for specific tasks and purposes Utilizing psychological research to design sys-tems in order to infer user intent Theory of mind research for autonomous systems regarding their human operators Simulated environments and agents in order to test the simulations in representative areas. Common-Sense reasoning augmented by Large Language Model technology for instructing ro-botic platforms The following things will be discussed at the poster ses-sion, representing a portfolio of ongoing work addressing the problems of large-scale multi-agent command and control. While the near-term application of these tech-nologies is into military problem domains; the poster presentation is cleared for public release.

Initial clinical outcomes of robotic resection for perihilar cholangiocarcinoma: Is it safe and effective?

We aimed to describe our outcomes of robotic resection for perihilar cholangiocarcinoma, the largest single institutional series in the Western hemisphere to date. Between 2016 and 2022, we prospectively followed all patients who underwent robotic resection for perihilar cholangiocarcinoma. In total, 23 patients underwent robotic resection for perihilar cholangiocarcinoma, 18 receiving concomitant hepatectomy. The median age was 73 years. Operative time was 470 min with an estimated blood loss of 150 mL. No intraoperative conversions to open or other intraoperative complications occurred. Median length of stay was 5 days. Four postoperative complications occurred. Three readmissions occurred within 30 days with one 90-day mortality. R0 resection was achieved in 87% of patients and R1 in 13% of patients. At a median follow-up of 27 months, 15 patients were alive without evidence of disease, two patients with local recurrence at 1 year, and six were deceased. Utilization of the robotic platform for perihilar cholangiocarcinoma is safe and feasible with excellent perioperative outcomes. Further studies are needed to determine the long-term oncological outcomes.

МЕТОД КОДУВАННЯ ВІДЕОДАНИХ В СПЕКТРАЛЬНО- ПАРАМЕТРИЧНОМУ ПРОСТОРІ

It is shown that the development of modern infocommunication systems is followed by the trend of widespread use of wireless technologies. The level of intellectualization of the protocols of their functioning is increasing. Accordingly, the characteristics of wireless infocommunication technologies for data transmission are increasing. This contributes to their use for data transmission from remote robotic platforms in the process of information support for the functioning of critical infrastructure. It is substantiated that the transmission of video data with the required level of bit intensity on the basis of existing on-board telecommunication technologies is organized under conditions of significant time delays. Consequently, the level of efficiency of information delivery is lost. On the other hand, there are losses in the reliability of video information. It is argued that the option for solving the problem lies in the further development of technologies for encoding video information streams. The most common platform is the JPEG format. However, the city has disadvantages. They refer to the loss of compression levels in the event of a reduction in the potential for detecting psychovisual addictions. The article substantiates an approach for improvement, which consists in the use of an adapted coding technology in the spectral-parametric space. This approach consists in detecting subbands in spectral arrays and their subsequent parameterization with the formation of structural components at a significant level and length. Further processing is proposed to be carried out taking into account the informativeness of segments and reducing the amount of structural redundancy. An approach for constructing a technology for compression of spectral arrays with the detection of spectral sub-bands is substantiated. A model has been created to find the amount of information for transformed segments in the spectral-parametric space. This takes into account the available amount of redundancy, which is established by determining the constraints on the values of structural components. A method for encoding segments in spectral-parametric description has been developed. The main basic components of the method relate to the processing of sets of two-component structural-parametric components, taking into account the peculiarities of their content depending on the presence of quantization processes.

First report of robotic retromuscular incisional hernia repair with Hugo Ras™ surgical system.

Treatment of incisional hernia is a rapidly evolving field of surgery, with actual trends being oriented toward retromuscular/preperitoneal mesh placement. The diffusion of robotic surgery is constantly growing in different surgical specialties and is gaining widespread acceptance for abdominal wall reconstruction. Recently, novel robotic platforms have entered into the market. In this study, we present the first transabdominal retromuscular incisional hernia repair performed with the new Hugo RAS™ system (Medtronic, Minneapolis, MN, USA). The surgical team had previous robotic experience and completed an official 2-day session running incisional hernia repair on human cadaver lab. Operating room setting and trocar layout were planned. The patient presented a 4 × 4cm midline incisional hernia and was scheduled for transabdominal retromuscular incisional hernia repair at our Institution. A description of the operative room setup, robotic arm configuration and docking/tilt angles is provided. Docking time, operative time, and console time were 15, 95, and 75min, respectively. All the surgical steps were completed without critical surgical errors or high-priority alarms. Neither intraoperative complications nor conversion to open surgery was recorded. Postoperative course was uneventful and the patient was discharged on postoperative day 2. The safety and the feasibility of these procedures will require further analysis and larger patients' sample sizes for procedural standardization and potential integration into minimally invasive abdominal wall reconstruction programs.

Mobile Robot + IoT: Project of Sustainable Technology for Sanitizing Broiler Poultry Litter.

The traditional aviary decontamination process involves farmers applying pesticides to the aviary's ground. These agricultural defenses are easily dispersed in the air, making the farmers susceptible to chronic diseases related to recurrent exposure. Industry 5.0 raises new pillars of research and innovation in transitioning to more sustainable, human-centric, and resilient companies. Based on these concepts, this paper presents a new aviary decontamination process that uses IoT and a robotic platform coupled with ozonizer (O3) and ultraviolet light (UVL). These clean technologies can successfully decontaminate poultry farms against pathogenic microorganisms, insects, and mites. Also, they can degrade toxic compounds used to control living organisms. This new decontamination process uses physicochemical information from the poultry litter through sensors installed in the environment, which allows accurate and safe disinfection. Different experimental tests were conducted to construct the system. First, tests related to measuring soil moisture, temperature, and pH were carried out, establishing the range of use and the confidence interval of the measurements. The robot's navigation uses a back-and-forth motion that parallels the aviary's longest side because it reduces the number of turns, reducing energy consumption. This task becomes more accessible because of the aviaries' standardized geometry. Furthermore, the prototype was tested in a real aviary to confirm the innovation, safety, and effectiveness of the proposal. Tests have shown that the UV + ozone combination is sufficient to disinfect this environment.

A falls recognition framework based on faster R-CNN and temporal action sequences that can be deployed on home service robots

With the popularity of home service robots (e.g. floor sweepers), robots should be considered to have more features for older adult care. Compared to fixed home monitors with a limited field of view, fall detection with service robots is an ideal solution to keep older adults and disabled people within sight. However, the user’s actions, such as lying on the bed to sleep or slumping on the sofa to rest, cause the traditional fall detection system to generate false alarms, which disrupts the user’s family life. The present work proposed an enhanced faster R-convolutional neural network (CNN) network by incorporating temporal action sequences and fall acceleration computation, demonstrating a reduced misjudgment rate on the service robot platform. Firstly, motion images were captured to obtain the target’s motion area description and action timing at the input stage. Then, the faster R-CNN algorithm was implemented to check the suspected falls further based on the falling acceleration of the detected actions during the training phase. Finally, the proposed temporal action sequences module eliminated the action mistaken for falling. Network training and robotic platform testing demonstrated that the proposed approach distinguished between falls and false alarms, which mitigated the occurrence of false positives. On the service robot platform, experimental results showed that the FAR was 8.19 and processing time was 0.79 s.

A Comparison of Myoelectric Control Modes for an Assistive Robotic Virtual Platform.

In this paper, we propose a daily living situation where objects in a kitchen can be grasped and stored in specific containers using a virtual robot arm operated by different myoelectric control modes. The main goal of this study is to prove the feasibility of providing virtual environments controlled through surface electromyography that can be used for the future training of people using prosthetics or with upper limb motor impairments. We propose that simple control algorithms can be a more natural and robust way to interact with prostheses and assistive robotics in general than complex multipurpose machine learning approaches. Additionally, we discuss the advantages and disadvantages of adding intelligence to the setup to automatically assist grasping activities. The results show very good performance across all participants who share similar opinions regarding the execution of each of the proposed control modes.

Improved Real-Time Models for Object Detection and Instance Segmentation for Agaricus bisporus Segmentation and Localization System Using RGB-D Panoramic Stitching Images

The segmentation and localization of Agaricus bisporus is a precondition for its automatic harvesting. A. bisporus growth clusters can present challenges for precise localization and segmentation because of adhesion and overlapping. A low-cost image stitching system is presented in this research, utilizing a quick stitching method with disparity correction to produce high-precision panoramic dual-modal fusion images. An enhanced technique called Real-Time Models for Object Detection and Instance Segmentation (RTMDet-Ins) is suggested. This approach utilizes SimAM Attention Module’s (SimAM) global attention mechanism and the lightweight feature fusion module Space-to-depth Progressive Asymmetric Feature Pyramid Network (SPD-PAFPN) to improve the detection capabilities for hidden A. bisporus. It efficiently deals with challenges related to intricate segmentation and inaccurate localization in complex obstacles and adhesion scenarios. The technology has been verified by 96 data sets collected on a self-designed fully automatic harvesting robot platform. Statistical analysis shows that the worldwide stitching error is below 2 mm in the area of 1200 mm × 400 mm. The segmentation method demonstrates an overall precision of 98.64%. The planar mean positioning error is merely 0.31%. The method promoted in this research demonstrates improved segmentation and localization accuracy in a challenging harvesting setting, enabling efficient autonomous harvesting of A. bisporus.

THE ROLE OF THE LATERAL ANKLE COMPLEX IN CONTROLLING LAXITY OF THE ANKLE JOINT: A BIOMECHANICAL INVESTIGATION

BackgroundLateral ankle instability is a common problem, but the precise role of the lateral ankle structures has not been accurately investigated. This study aimed to accurately investigate lateral ankle complex stability for the first time using a novel robotic testing platform.MethodA six degrees of freedom robot manipulator and a universal force/torque sensor were used to test 10 foot and ankle specimens. The system automatically defined the path of unloaded plantar/dorsi flexion. At four flexion angles: 20° dorsiflexion, neutral flexion, 20° and 40° of plantarflexion; anterior-posterior (90N), internal-external (5Nm) and inversion-eversion (8Nm) laxity were tested. The motion of the intact ankle was recorded first and then replayed following transection of the lateral retinaculum, Anterior Talofibular Ligament (ATFL) and Calcaneofibular Ligament (CFL). The decrease in force/torque reflected the contribution of the structure to restraining laxity. Data were analysed using repeated measures of variance and paired t-tests.ResultsThe ATFL was the primary restraint to anterior drawer (P< 0.01) and the CFL the primary restraint to inversion throughout range (P< 0.04), but with increased plantarflexion the ATFL's contribution increased. The ATFL had a significant role in resisting tibial external rotation, particularly at higher levels of plantarflexion, contributing 63% at 40° (P< 0.01). The CFL provided the greatest resistance to external tibial rotation, 22% at 40° plantarflexion (P< 0.01). The extensor retinaculum and skin did not offer significant restraint in any direction tested.ConclusionThis study shows accurately for the first time the significant role the ATFL and CFL have in rotational ankle stability. This significant loss in rotational stability may have implications in the aetiology of osteophyte formation and early degenerative changes in patients with chronic ankle instability. This is the first time the role of the lateral ankle complex has been quantified using a robotic testing platform.

Learning Curve of Robotic End-to-Side Microanastomoses.

Robotics are becoming increasingly widespread within various neurosurgical subspecialties, but data pertaining to their feasibility in vascular neurosurgery are limited. We present our novel attempt to evaluate the learning curve of a robotic platform for microvascular anastomoses. One hundred and sixty one sutures were performed and assessed. Fourteen anastomoses (10 robotic [MUSA-2 Microsurgical system; Microsure] and 4 hand-sewn) were performed by the senior author on 1.5-mm caliber tubes and recorded with the Kinevo 900 (Zeiss) operative microscope. We separately compared interrupted sutures (from needle insertion until third knot) and running sutures (from needle insertion until loop pull-down). Average suture timing across all groups was compared using an unpaired Student's t test. Exponential smoothing (α = 0.2) was then applied to the robotic data sets for validation and a second set of t tests were performed. We compared 107 robotic sutures with 54 hand-sewn sutures. There was a significant difference between the average time/stitch for the robotic running sutures (n = 55) and the hand-sewn running sutures (n = 31) (31.2 seconds vs 48.3 seconds, respectively; P-value = .00052). Exponential smoothing (α = 0.2) reinforced these results (37.6 seconds vs 48.3 seconds; P-value = .014625). Average robotic running times surpassed hand-sewn by the second anastomosis (38.8 seconds vs 48.3 seconds) and continued to steadily decrease with subsequent stitches. The average of the robotic interrupted sutures (n = 52) was significantly longer than the hand-sewn (n = 23) (171.3 seconds vs 70 seconds; P = .000024). Exponential smoothing (α = 0.2) yielded similar results (196.7 seconds vs 70 seconds; P = .00001). However, average robotic interrupted times significantly decreased from the first to the final anastomosis (286 seconds vs 105.2 seconds; P = .003674). Our results indicate the learning curve for robotic microanastomoses is short and encouraging. The use of robotics warrants further study for potential use in cerebrovascular bypass procedures.

Active visual continuous seam tracking based on adaptive feature detection and particle filter tracking

Welding seam tracking based on online programming is the future trend of intelligent production. However, most of the existing image processing methods have certain limitations in the adaptability, accuracy, and robustness of weld feature point detection. The online welding method of gas metal arc welding (GMAW) based on active vision sensing is studied in this paper. The Steger sub-pixel detection method is used to guarantee the accuracy of feature point extraction, and a self-adaptive search window and self-adaptive slope extraction are proposed on this basis. The self-adaptive window is generated according to the linear information of the weld area, and the scale factor and range threshold constraint are added to realize the real-time detection of the weld feature information. Screening the center pixel of the laser stripe in the self-adaptive window of the current frame by the initial slope or the self-adaptive slope of the previous frame, the linear information of the weld area is obtained. The self-adaptive slope of the current frame is fitted by the random sampling consistency method, and the pixel margin is retained to adapt to the linear detection of different continuous welds. When arc light and other serious interference make it difficult to obtain weld information, a particle filter is used to make the best prediction of the weld position. Finally, the welding robot platform based on laser vision sensing was built to test various continuous welds of the butt weld, fillet weld, and lap weld. Experimental results show that the detection speed is 27 ms, and the accuracy of detection and tracking can respectively reach 0.03 mm and 0.78 mm, which meets the requirements of weld detection and tracking.

Modeling, Analysis and Evaluation of a Novel Compact 6-DoF 3-RRRS Needle Biopsy Robot

Robot-assisted surgical systems have been widely applied for minimally invasive needle biopsies thanks to their excellent accuracy and superior stability compared to manual surgical operations, which lead to possible fatigue and misoperation due to long procedures. Current needle biopsy robots are normally customed designed for specific application scenarios, and only position-level kinematics are derived, preventing advanced speed control or singularity analysis. As a step forward, this paper aims to design a universal needle biopsy robot platform which features 6 DoF 3-RRRS (Revolute–Revolute–Revolute–Spherical) parallel structure. The analytical solutions to its nonlinear kinematic problems, including forward kinematics, inverse kinematics, and differential kinematics are derived, allowing fast and accurate feedback control calculations. A multibody simulation platform and a first-generation prototype are established next to provide comprehensive verifications for the derived robotic model. Finally, simulated puncture experiments are carried out to illustrate the effectiveness of the proposed method.

Asymmetric fin shape changes swimming dynamics of ancient marine reptiles’ soft robophysical models

Animals have evolved highly effective locomotion capabilities in terrestrial, aerial, and aquatic environments. Over life’s history, mass extinctions have wiped out unique animal species with specialized adaptations, leaving paleontologists to reconstruct their locomotion through fossil analysis. Despite advancements, little is known about how extinct megafauna, such as the Ichthyosauria one of the most successful lineages of marine reptiles, utilized their varied morphologies for swimming. Traditional robotics struggle to mimic extinct locomotion effectively, but the emerging soft robotics field offers a promising alternative to overcome this challenge. This paper aims to bridge this gap by studying Mixosaurus locomotion with soft robotics, combining material modeling and biomechanics in physical experimental validation. Combining a soft body with soft pneumatic actuators, the soft robotic platform described in this study investigates the correlation between asymmetrical fins and buoyancy by recreating the pitch torque generated by extinct swimming animals. We performed a comparative analysis of thrust and torque generated by Carthorhyncus, Utatsusaurus, Mixosaurus, Guizhouichthyosaurus, and Ophthalmosaurus tail fins in a flow tank. Experimental results suggest that the pitch torque on the torso generated by hypocercal fin shapes such as found in model systems of Guizhouichthyosaurus, Mixosaurus and Utatsusaurus produce distinct ventral body pitch effects able to mitigate the animal’s non-neutral buoyancy. This body pitch control effect is particularly pronounced in Guizhouichthyosaurus, which results suggest would have been able to generate high ventral pitch torque on the torso to compensate for its positive buoyancy. By contrast, homocercal fin shapes may not have been conducive for such buoyancy compensation, leaving torso pitch control to pectoral fins, for example. Across the range of the actuation frequencies of the caudal fins tested, resulted in oscillatory modes arising, which in turn can affect the for-aft thrust generated.

Robotic transversus abdominis release using HUGO RAS system: our initial experience.

Transversus abdominis release (TAR) is an effective technique for treating large midline and off-midline hernias. Recent studies have demonstrated that robotic TAR (rTAR) is technically feasible and associated with improved outcomes compared to open surgery. There is no published experience to date describing abdominal wall reconstruction using the novel robotic platform HUGO RAS System (Medtronic®). All consecutive patients who underwent a rTAR in our institution were included. Three of the four arm carts of the HUGO RAS System were used at any given time. Each arm configuration was defined by our team in conjunction with Medtronic® personnel. rTAR was performed as previously described. Upon completion of the TAR on one side, a redocking process with different, mirrored arms angles was performed to continue with the contralateral TAR. Operative variables and early morbidity were recorded. Ten patients were included in this study. The median BMI was 31 (21-40.6) kg/m2. The median height was 1.6m (1.5-1.89m). A trend of decreased operative time, console time, and redocking time was seen in these consecutive cases. No intraoperative events nor postoperative morbidity was reported. The median length of stay was 3 (1-6) days. Robotic TAR utilizing the HUGO RAS system is a feasible and safe procedure. The adoption of this procedure on this novel platform for the treatment of complex abdominal wall hernias has been successful for our team.

A Real-to-Sim-to-Real Approach for Vision-Based Autonomous MAV-Catching-MAV

This paper studies the task of vision-based MAV-catching-MAV, where a catcher MAV (micro aerial vehicle) can detect, localize, and pursue a target MAV autonomously. Since it is challenging to develop detectors that can effectively detect unseen MAVs in complex environments, the main novelty of this paper is to propose a real-to-sim-to-real approach to address this challenge. In this method, images of real-world environments are first collected. Then, these images are used to construct a high-fidelity simulation environment, based on which a deep-learning detector is trained. The merit of this approach is that it allows efficient automatic collection of large-scale and high-quality labeled datasets. More importantly, since the simulation environment is constructed from real-world images, this approach can effectively bridge the sim-to-real gap, enabling efficient deployment in real environments. Another contribution of this paper lies in the successful implementation of a fully autonomous vision-based MAV-catching-MAV system including proposed estimation and pursuit control algorithms. While the previous works mainly focused on certain aspects of this system, we developed a completely autonomous system that integrates detection, estimation, and control algorithms on real-world robotic platforms.

A Bioinspired Control Strategy Ensures Maneuverability and Adaptability for Dynamic Environments in an Underactuated Robotic Fish

Bioinspired underwater robots can move efficiently, with agility, even in complex aquatic areas, reducing marine ecosystem disturbance during exploration and inspection. These robots can improve animal farming conditions and preserve wildlife. This study proposes a muscle-like control for an underactuated robot in carangiform swimming mode. The artifact exploits a single DC motor with a non-blocking transmission system to convert the motor’s oscillatory motion into the fishtail’s oscillation. The transmission system combines a magnetic coupling and a wire-driven mechanism. The control strategy was inspired by central pattern generators (CPGs) to control the torque exerted on the fishtail. It integrates proprioceptive sensory feedback to investigate the adaptability to different contexts. A parametrized control law relates the reference target to the fishtail’s angular position. Several tests were carried out to validate the control strategy. The proprioceptive feedback revealed that the controller can adapt to different environments and tail structure changes. The control law parameters variation accesses the robotic fish’s multi-modal swimming. Our solution can vary the swimming speed of 0.08 body lengths per second (BL/s), and change the steering direction and performance by an angular speed and turning curvature radius of 0.08 rad/s and 0.25 m, respectively. Performance can be improved with design changes, while still maintaining the developed control strategy. This approach ensures the robot’s maneuverability despite its underactuated structure. Energy consumption was evaluated under the robotic platform’s control and design. Our bioinspired control system offers an effective, reliable, and sustainable solution for exploring and monitoring aquatic environments, while minimizing human risks and preserving the ecosystem. Additionally, it creates new and innovative opportunities for interacting with marine species. Our findings demonstrate the potential of bioinspired technologies to advance the field of marine science and conservation.

ASO Author Reflections: The Role of Robotic Surgery on Central Pancreatectomy.

Central pancreatectomy (CP) is indicated for benign or low-grade pancreatic tumors located in the neck or proximal pancreatic body. This procedure is demanding and has a high rate of postoperative complications. Minimally invasive surgery is now commonly used for CP but it is still unclear whether the robotic approach offers any advantages over conventional pancreatic minimally invasive surgery. Most studies on robotic CP are limited to case reports or case series; however, there are two important studies on this topic. Currently, the evidence on robotic CP remains limited, making it challenging to draw definitive conclusions in favor of one technique over the other. The use of a robotic platform, with its integrated tools such as intraoperative ultrasound, can guide the surgeon in performing this technically demanding procedure in a safer manner. The controversy regarding the best minimally invasive surgery approach for CP is still ongoing and requires further research.