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

Characterization of signal kinetics in real time surgical tissue classification system

Effective surgical margin assessment is paramount for good oncological outcomes and new methods are in active development. One emerging approach is the analysis of the chemical composition of surgical smoke from tissues. Surgical smoke is typically removed with a smoke evacuator to protect the operating room staff from its harmful effects to the respiratory system. Thus, analysis of the evacuated smoke without disturbing the operation is a feasible approach. Smoke transportation is subject to lags that affect system usability. We analyzed the smoke transportation delay and evaluated its effects to tissue classification with differential mobility spectrometry in a simulated setting using porcine tissues. With a typical smoke evacuator setting, the front of the surgical plume reaches the analysis system in 380 ms and the sensor within one second. For a typical surgical incision (duration 1.5 s), the measured signal reaches its maximum in 2.3 s and declines to under 10% of the maximum in 8.6 s from the start of the incision. Two-class tissue classification was tested with 2, 3, 5, and 11 s repetition rates resulting in no significant differences in classification accuracy, implicating that signal retention from previous samples is mitigated by the classification algorithm.publishedVersionPeer reviewe

Teleoperation Methods for High-Risk, High-Latency Environments

In-Space Servicing, Assembly, and Manufacturing (ISAM) can enable larger-scale and longer-lived infrastructure projects in space, with interest ranging from commercial entities to the US government. Servicing, in particular, has the potential to vastly increase the usable lifetimes of satellites. However, the vast majority of spacecraft on low Earth orbit today were not designed to be serviced on-orbit. As such, several of the manipulations during servicing cannot easily be automated and instead require ground-based teleoperation. Ground-based teleoperation of on-orbit robots brings its own challenges of high latency communications, with telemetry delays of several seconds, and difficulties in visualizing the remote environment due to limited camera views. We explore teleoperation methods to alleviate these difficulties, increase task success, and reduce operator load. First, we investigate a model-based teleoperation interface intended to provide the benefits of direct teleoperation even in the presence of time delay. We evaluate the model-based teleoperation method using professional robot operators, then use feedback from that study to inform the design of a visual planning tool for this task, Interactive Planning and Supervised Execution (IPSE). We describe and evaluate the IPSE system and two interfaces, one 2D using a traditional mouse and keyboard and one 3D using an Intuitive Surgical da Vinci master console. We then describe and evaluate an alternative 3D interface using a Meta Quest head-mounted display. Finally, we describe an extension of IPSE to allow human-in-the-loop planning for a redundant robot. Overall, we find that IPSE improves task success rate and decreases operator workload compared to a conventional teleoperation interface

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

Accelerating Surgical Robotics Research: A Review of 10 Years With the da Vinci Research Kit

Robotic-assisted surgery is now well-established in clinical practice and has become the gold standard clinical treatment option for several clinical indications. The field of robotic-assisted surgery is expected to grow substantially in the next decade with a range of new robotic devices emerging to address unmet clinical needs across different specialities. A vibrant surgical robotics research community is pivotal for conceptualizing such new systems as well as for developing and training the engineers and scientists to translate them into practice. The da Vinci Research Kit (dVRK), an academic and industry collaborative effort to re-purpose decommissioned da Vinci surgical systems (Intuitive Surgical Inc, CA, USA) as a research platform for surgical robotics research, has been a key initiative for addressing a barrier to entry for new research groups in surgical robotics. In this paper, we present an extensive review of the publications that have been facilitated by the dVRK over the past decade. We classify research efforts into different categories and outline some of the major challenges and needs for the robotics community to maintain this initiative and build upon it

ROS based Teleoperation and Docking of a Low Speed Urban Vehicle

In recent years, 4G LTE technology has provided us with higher than ever transfer speeds over the cellular networks, permitting streaming of video and other high bandwidth services. On the other hand, there has been a rapid development and an explosion of interest in frameworks for robot software development, particularly ROS. Though there have been many studies which have leveraged 4G LTE network as the mode of communication when studying teleoperations, a very few studies have used 4G LTE network with ROS framework for building teleoperated systems. Therefore, this study seeks to build a teleoperated system using the ROS framework which employs the 4G LTE network for communication. For this purpose, a prototype system is built using a remote-controlled low speed urban vehicle that hosts a multimedia link between the vehicle and the control station. The operator drives the vehicle remotely primarily based on processed video feed and LIDAR data. The vehicle is also equipped with safety systems to avoid collisions. The teleoperated system built is tested by asking an experienced driver to complete certain tasks while driving the vehicle remotely. Moreover, this study also intends to build an autonomous docking procedure for the vehicle. A docking procedure based on differential GPS and video feedback is built that allows the vehicle to autonomously dock itself into a charging station. The procedure provides a proof of concept solution for the autonomous charging/fueling of self-driving cars.  M.S

Augmented Reality Navigation Interfaces Improve Human Performance In End-Effector Controlled Telerobotics

On the International Space Station (ISS) and space shuttles, the National Aeronautics and Space Administration (NASA) has used robotic manipulators extensively to perform payload handling and maintenance tasks. Teleoperating robots require expert skills and optimal performance is crucial to mission completion and crew safety. Degradation in performance is observed when manual control is mediated through remote camera views, resulting in poor end-effector navigation quality and extended task completion times. This thesis explores the application of three-dimensional augmented reality (AR) interfaces specifically designed to improve human performance during end-effector controlled teleoperations. A modular telerobotic test bed was developed for this purpose and several experiments were conducted. In the first experiment, the effect of camera placement on end-effector manipulation performance was evaluated. Results show that increasing misalignment between the displayed end-effector and hand-controller axes (display-control misalignments) increases the time required to process a movement input. Simple AR movement cues were found to mitigate the adverse effects of camera-based teleoperation and made performance invariant to misalignment. Applying these movement cues to payload transport tasks correspondingly demonstrated improvements in free-space navigation quality over conventional end-effector control using multiple cameras. Collision-free teleoperations are also a critical requirement in space. To help the operators guide robots safely, a novel method was evaluated. Navigation plans computed by a planning agent are presented to the operator sequentially through an AR interface. The plans in combination with the interface allow the operator to guide the end-effector through collision-free regions in the remote environment safely. Experimental results show significant benefits in control performance including reduced path deviation and travel distance. Overall, the results show that AR interfaces can improve performance during manual control of remote robots and have tremendous potential in current and future teleoperated space robotic systems; as well as in contemporary military and surgical applications

Model Driven Robotic Assistance for Human-Robot Collaboration

While robots routinely perform complex assembly tasks in highly structured factory environments, it is challenging to apply completely autonomous robotic systems in less structured manipulation tasks, such as surgery and machine assembly/repair, due to the limitations of machine intelligence, sensor data interpretation and environment modeling. A practical, yet effective approach to accomplish these tasks is through human-robot collaboration, in which the human operator and the robot form a partnership and complement each other in performing a complex task. We recognize that humans excel at determining task goals and recognizing constraints, if given sufficient feedback about the interaction between the tool (e.g., end-effector of the robot) and the environment. Robots are precise, unaffected by fatigue and able to work in environments not suitable for humans. We hypothesize that by providing the operator with adequate information about the task, through visual and force (haptic) feedback, the operator can: (1) define the task model, in terms of task goals and virtual fixture constraints through an interactive, or immersive augmented reality interface, and (2) have the robot actively assist the operator to enhance the execution time, quality and precision of the tasks. We validate our approaches through the implementations of both cooperative (i.e., hands-on) control and telerobotic systems, for image-guided robotic neurosurgery and telerobotic manipulation tasks for satellite servicing under significant time delay

Complementary Situational Awareness for an Intelligent Telerobotic Surgical Assistant System

Robotic surgical systems have contributed greatly to the advancement of Minimally Invasive Surgeries (MIS). More specifically, telesurgical robots have provided enhanced dexterity to surgeons performing MIS procedures. However, current robotic teleoperated systems have only limited situational awareness of the patient anatomy and surgical environment that would typically be available to a surgeon in an open surgery. Although the endoscopic view enhances the visualization of the anatomy, perceptual understanding of the environment and anatomy is still lacking due to the absence of sensory feedback. In this work, these limitations are addressed by developing a computational framework to provide Complementary Situational Awareness (CSA) in a surgical assistant. This framework aims at improving the human-robot relationship by providing elaborate guidance and sensory feedback capabilities for the surgeon in complex MIS procedures. Unlike traditional teleoperation, this framework enables the user to telemanipulate the situational model in a virtual environment and uses that information to command the slave robot with appropriate admittance gains and environmental constraints. Simultaneously, the situational model is updated based on interaction of the slave robot with the task space environment. However, developing such a system to provide real-time situational awareness requires that many technical challenges be met. To estimate intraoperative organ information continuous palpation primitives are required. Intraoperative surface information needs to be estimated in real-time while the organ is being palpated/scanned. The model of the task environment needs to be updated in near real-time using the estimated organ geometry so that the force-feedback applied on the surgeon's hand would correspond to the actual location of the model. This work presents a real-time framework that meets these requirements/challenges to provide situational awareness of the environment in the task space. Further, visual feedback is also provided for the surgeon/developer to view the near video frame rate updates of the task model. All these functions are executed in parallel and need to have a synchronized data exchange. The system is very portable and can be incorporated to any existing telerobotic platforms with minimal overhead