Network Latency in Teleoperation of Connected and Autonomous Vehicles:A Review of Trends, Challenges, and Mitigation Strategies

With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs

Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases

Certain telerobotic applications, including telerobotics in space, pose particularly demanding challenges to both technology and humans. Traditional bilateral telemanipulation approaches often cannot be used in such applications due to technical and physical limitations such as long and varying delays, packet loss, and limited bandwidth, as well as high reliability, precision, and task duration requirements. In order to close this gap, we research model-augmented haptic telemanipulation (MATM) that uses two kinds of models: a remote model that enables shared autonomous functionality of the teleoperated robot, and a local model that aims to generate assistive augmented haptic feedback for the human operator. Several technological methods that form the backbone of the MATM approach have already been successfully demonstrated in accomplished telerobotic space missions. On this basis, we have applied our approach in more recent research to applications in the fields of orbital robotics, telesurgery, caregiving, and telenavigation. In the course of this work, we have advanced specific aspects of the approach that were of particular importance for each respective application, especially shared autonomy, and haptic augmentation. This overview paper discusses the MATM approach in detail, presents the latest research results of the various technologies encompassed within this approach, provides a retrospective of DLR's telerobotic space missions, demonstrates the broad application potential of MATM based on the aforementioned use cases, and outlines lessons learned and open challenges

The future of robotic surgery

© 2018 Royal College of Surgeons.For 20 years Intuitive Surgical’s da Vinci® system has held the monopoly in minimally invasive robotic surgery. Restrictive patenting, a well-developed marketing strategy and a high-quality product have protected the company’s leading market share.1 However, owing to the nuances of US patenting law, many of Intuitive Surgical’s earliest patents will be expiring in the next couple of years. With such a shift in backdrop, many of Intuitive Surgical’s competitors (from medical and industrial robotic backgrounds) have initiated robotic programmes – some of which are available for clinical use now. The next section of the review will focus on new and developing robotic systems in the field of minimally invasive surgery (Table 1), single-site surgery (Table 2), natural orifice transluminal endoscopic surgery (NOTES) and non-minimally invasive robotic systems (Table 3).Peer reviewedFinal Published versio

Network Digital Twin: Context, Enabling Technologies and Opportunities

The proliferation of emergent network applications (e.g., telesurgery, metaverse) is increasing the difficulty of managing modern communication networks. These applications entail stringent network requirements (e.g., ultra-low deterministic latency), which hinders network operators to manage their resources efficiently. In this article, we introduce the network digital twin (NDT), a renovated concept of classical network modeling tools whose goal is to build accurate data-driven network models that can operate in real-time. We describe the general architecture of the NDT and argue that modern machine learning (ML) technologies enable building some of its core components. Then, we present a case study that leverages a ML-based NDT for network performance evaluation and apply it to routing optimization in a QoS-aware use case. Lastly, we describe some key open challenges and research opportunities yet to be explored to achieve effective deployment of NDTs in real-world networks.Comment: 7 pages, 4 figures. arXiv admin note: text overlap with arXiv:2201.0114

Development and applicability of a soft and flexible robotic arm in digestive surgery

Introduction The oncologic adequacy of laparoscopy in digestive surgery is still controversial, especially in some technically demanding operations like Total Mesorectal Excision (TME). Even if standard robotic platforms, i.e. the da Vinci Surgical System, can improve dexterity and manouvrability of surgical instruments, there is no evidence supporting its use in digestive and rectal cancer surgery. The only multi-centre prospective RCT (ROLARR trial) suggests that robotic TME has no advantages compared to laparoscopic TME in terms of clinical and oncologic outcomes. A possible explanation of this lack of real advantages is that the articulation is possible only on the tip of the instrument. The opportunity to have a robotic platform with modular flexibility on the whole length of the arm could overcome technical limitations, improving results and allowing standardization and diffusion of the procedures. Methods The 7FP STIFF FLOP project was financed by the European Commission in order to develop a STIFFness controllable Flexible and Learn-able manipulator for surgical operations. Engineers were inspired by the tentacles of an octopus. A prototype was realized, consisting of multiple soft, pneumatically actuated threechamber segments. Additional chambers are integrated within the segments to allow their stiffening, employing an approach based on the concept of granular jamming. The STIFF-FLOP segments are actuated using pressure regulators and the stiffening chambers are interfaced via valves, applying a vacuum to the granules in the chambers. Sensors are embedded in the STIFF-FLOP modules to measure interaction forces (between the robot and its environment) and the robot’s configuration. A newly developed user interface, based on a Delta robot design, is used to move and position the tip of the STIFF-FLOP arm inside the abdomen. Signals obtained from sensors are fed back to the user interface console providing the operator with force feedback. The entire soft robot is equipped with a 4 mm in diameter centre-free lumen, which allows the passage of the electrical wires needed for the laparoscopic miniaturized optic system positioned at the tip of the robot. Phantom test The prototype was tested in order to assess learnability and satisfaction of the operators. The test was designed as a spatial motion task, consisting of movements between predefined target points clockwise and counter clockwise in a 3D phantom of the abdominal cavity. The participants were asked to conclude the task for the first time with the STIFF-FLOP prototype (SF1), then to repeat the task using conventional laparoscopic instrumentation (LAP) and finally to perform the task once more with the STIFF-FLOP arm (SF2). Surface EMG signals from the forearm muscles were recorded during the test. Results SF1 took a longer time than the other tasks, i.e. 36.4% more than LAP (p=0.0071). However, from SF1 to SF2 there was a 32.1% time reduction (p=0.0232). EMG amplitude analysis showed a higher overall average muscle activity during LAP. Moving from LAP to SF2 there was a 25.9% reduction in average muscle activity (p=0.0128). Cadaver test. The main objective of the test was to validate the compatibility of the system with human anatomy for laparoscopic TME and to determine whether the soft robot could represent a potential improvement compared to standard rigid laparoscopic instrumentation. The study was performed on two cadavers prepared according to the method described by Thiel. Results The use of the STIFF-FLOP camera allowed the surgeon to clearly visualize the inferior mesenteric vessels and the autonomic nerves that were subsequently spared from injury. The ability to smoothly follow the sacral curve due to the flexibility of the manipulator allowed the surgeons to perform a very precise dissection of the posterior part of the mesorectum. The same procedure was performed on both human cadavers, demonstrating the ease of use of the system. Completion times of the procedure were 165 and 145 min, respectively. No intraoperative complications were recorded. No technical failures were registered. Conclusion The STIFF FLOP flexible robotic arm is an intuitive technology that can be easily learned. The prolonged use of the STIFF FLOP manipulator is more comfortable than standard laparoscopic instrumentation and can be used for a long time without exhaustion. The system is compatible with human anatomy and allows to perform a standard surgical abdominal operation. The STIFF FLOP arm seems to improve visualization of the operatory field especially in narrow spaces like the pelvis

Minimally Invasive Expeditionary Surgical Care Using Human-Inspired Robots

This technical report serves as an updated collection of subject matter experts on surgical care using human-inspired robotics for human exploration. It is a summary of the Blue Sky Meeting, organized by the Florida Institute for Human and Machine Cognition (IHMC), Pensacola, Florida, and held on October 2-3, 2018. It contains an executive summary, the final report, all of the presentation materials, and an updated reference list

A Comprehensive Survey of the Tactile Internet: State of the art and Research Directions

The Internet has made several giant leaps over the years, from a fixed to a mobile Internet, then to the Internet of Things, and now to a Tactile Internet. The Tactile Internet goes far beyond data, audio and video delivery over fixed and mobile networks, and even beyond allowing communication and collaboration among things. It is expected to enable haptic communication and allow skill set delivery over networks. Some examples of potential applications are tele-surgery, vehicle fleets, augmented reality and industrial process automation. Several papers already cover many of the Tactile Internet-related concepts and technologies, such as haptic codecs, applications, and supporting technologies. However, none of them offers a comprehensive survey of the Tactile Internet, including its architectures and algorithms. Furthermore, none of them provides a systematic and critical review of the existing solutions. To address these lacunae, we provide a comprehensive survey of the architectures and algorithms proposed to date for the Tactile Internet. In addition, we critically review them using a well-defined set of requirements and discuss some of the lessons learned as well as the most promising research directions

Modeling of Force and Motion Transmission in Tendon-Driven Surgical Robots

Tendon-based transmission is a common approach for transferring motion and forces in surgical robots. In spite of design simplicity and compactness that comes with the tendon drives, there exists a number of issues associated with the tendon-based transmission. In particular, the elasticity of the tendons and the frictional interaction between the tendon and the routing result in substantially nonlinear behavior. Also, in surgical applications, the distal joints of the robot and instruments cannot be sensorized in most cases due to technical limitations. Therefore, direct measurement of forces and use of feedback motion/force control for compensation of uncertainties in tendon-based motion and force transmission are not possible. However, force/motion estimation and control in tendon-based robots are important in view of the need for haptic feedback in robotic surgery and growing interest in automatizing common surgical tasks. One possible solution to the above-described problem is the development of mathematical models for tendon-based force and motion transmission that can be used for estimation and control purposes. This thesis provides analysis of force and motion transmission in tendon-pulley based surgical robots and addresses various aspects of the transmission modeling problem. Due to similarities between the quasi-static hysteretic behavior of a tendon-pulley based da Vinci® instrument and that of a typical tendon-sheath mechanism, a distributed friction approach for modeling the force transmission in the instrument is developed. The approach is extended to derive a formula for the apparent stiffness of the instrument. Consequently, a method is developed that uses the formula for apparent stiffness of the instrument to determine the stiffness distribution of the tissue palpated. The force transmission hysteresis is further investigated from a phenomenological point of view. It is shown that a classic Preisach hysteresis model can accurately describe the quasi-static input-output force transmission behavior of the da Vinci® instrument. Also, in order to describe the distributed friction effect in tendon-pulley mechanisms, the creep theory from belt mechanics is adopted for the robotic applications. As a result, a novel motion transmission model is suggested for tendon-pulley mechanisms. The developed model is of pseudo-kinematic type as it relates the output displacement to both the input displacement and the input force. The model is subsequently used for position control of the tip of the instrument. Furthermore, the proposed pseudo-kinematic model is extended to compensate for the coupled-hysteresis effect in a multi-DOF motion. A dynamic transmission model is also suggested that describes system’s response to high frequency inputs. Finally, the proposed motion transmission model was used for modeling of the backlash-like hysteresis in RAVEN II surgical robot