2,000 research outputs found
Prevalence of haptic feedback in robot-mediated surgery : a systematic review of literature
© 2017 Springer-Verlag. This is a post-peer-review, pre-copyedit version of an article published in Journal of Robotic Surgery. The final authenticated version is available online at: https://doi.org/10.1007/s11701-017-0763-4With the successful uptake and inclusion of robotic systems in minimally invasive surgery and with the increasing application of robotic surgery (RS) in numerous surgical specialities worldwide, there is now a need to develop and enhance the technology further. One such improvement is the implementation and amalgamation of haptic feedback technology into RS which will permit the operating surgeon on the console to receive haptic information on the type of tissue being operated on. The main advantage of using this is to allow the operating surgeon to feel and control the amount of force applied to different tissues during surgery thus minimising the risk of tissue damage due to both the direct and indirect effects of excessive tissue force or tension being applied during RS. We performed a two-rater systematic review to identify the latest developments and potential avenues of improving technology in the application and implementation of haptic feedback technology to the operating surgeon on the console during RS. This review provides a summary of technological enhancements in RS, considering different stages of work, from proof of concept to cadaver tissue testing, surgery in animals, and finally real implementation in surgical practice. We identify that at the time of this review, while there is a unanimous agreement regarding need for haptic and tactile feedback, there are no solutions or products available that address this need. There is a scope and need for new developments in haptic augmentation for robot-mediated surgery with the aim of improving patient care and robotic surgical technology further.Peer reviewe
New Mechatronic Systems for the Diagnosis and Treatment of Cancer
Both two dimensional (2D) and three dimensional (3D) imaging modalities are useful tools for viewing the internal anatomy. Three dimensional imaging techniques are required for accurate targeting of needles. This improves the efficiency and control over the intervention as the high temporal resolution of medical images can be used to validate the location of needle and target in real time. Relying on imaging alone, however, means the intervention is still operator dependent because of the difficulty of controlling the location of the needle within the image. The objective of this thesis is to improve the accuracy and repeatability of needle-based interventions over conventional techniques: both manual and automated techniques. This includes increasing the accuracy and repeatability of these procedures in order to minimize the invasiveness of the procedure.
In this thesis, I propose that by combining the remote center of motion concept using spherical linkage components into a passive or semi-automated device, the physician will have a useful tracking and guidance system at their disposal in a package, which is less threatening than a robot to both the patient and physician. This design concept offers both the manipulative transparency of a freehand system, and tremor reduction through scaling currently offered in automated systems. In addressing each objective of this thesis, a number of novel mechanical designs incorporating an remote center of motion architecture with varying degrees of freedom have been presented. Each of these designs can be deployed in a variety of imaging modalities and clinical applications, ranging from preclinical to human interventions, with an accuracy of control in the millimeter to sub-millimeter range
INTEGRATION OF ROBOTIC AND ELECTRO-PNEUMATIC SYSTEMS USING ADVANCED CONTROL AND COMMUNICATION SCHEMES
Modern industrial automation systems are designed by interconnecting various subsystems which work together to perform a process. The thesis project aims to integrate fragmented subsystems into a flexible and reconfigurable system through advanced communication protocols and perform a process to demonstrate the effectiveness of interconnected systems.
The system consists of three six-axis robots, one electro-pneumatic robot, and two conveyors connected using EthernetIP communication and hardwired connections. The interconnected system works together to perform machining of a workpiece using advanced control methods of CAD to robot path generation, central control through a PLC, and process control through HMI.
Standardized programming blocks and HMI interfaces were developed to make the system highly reconfigurable and flexible for any future projects. The knowledge gained from the project is used to create lab manuals to educate students about communication and control methods for systems integration
Towards the development of safe, collaborative robotic freehand ultrasound
The use of robotics in medicine is of growing importance for modern health services, as robotic systems have the capacity to improve upon human tasks, thereby enhancing the treatment ability of a healthcare provider. In the medical sector, ultrasound imaging is an inexpensive approach without the high radiation emissions often associated with other modalities, especially when compared to MRI and CT imaging respectively. Over the past two decades, considerable effort has been invested into freehand ultrasound robotics research and development.
However, this research has focused on the feasibility of the application, not the robotic fundamentals, such as motion control, calibration, and contextual awareness. Instead, much of the work is concentrated on custom designed robots, ultrasound image generation and visual servoing, or teleoperation. Research based on these topics often suffer from important limitations that impede their use in an adaptable, scalable, and real-world manner. Particularly, while custom robots may be designed for a specific application, commercial collaborative robots are a more robust and economical solution. Otherwise, various robotic ultrasound studies have shown the feasibility of using basic force control, but rarely explore controller tuning in the context of patient safety and deformable skin in an unstructured environment. Moreover, many studies evaluate novel visual servoing approaches, but do not consider the practicality of relying on external measurement devices for motion control. These studies neglect the importance of robot accuracy and calibration, which allow a system to safely navigate its environment while reducing the imaging errors associated with positioning. Hence, while the feasibility of robotic ultrasound has been the focal point in previous studies, there is a lack of attention to what occurs between system design and image output.
This thesis addresses limitations of the current literature through three distinct contributions. Given the force-controlled nature of an ultrasound robot, the first contribution presents a closed-loop calibration approach using impedance control and low-cost equipment. Accuracy is a fundamental requirement for high-quality ultrasound image generation and targeting. This is especially true when following a specified path along a patient or synthesizing 2D slices into a 3D ultrasound image. However, even though most industrial robots are inherently precise, they are not necessarily accurate. While robot calibration itself has been extensively studied, many of the approaches rely on expensive and highly delicate equipment. Experimental testing showed that this method is comparable in quality to traditional calibration using a laser tracker. As demonstrated through an experimental study and validated with a laser tracker, the absolute accuracy of a collaborative robot was improved to a maximum error of 0.990mm, representing a 58.4% improvement when compared to the nominal model.
The second contribution explores collisions and contact events, as they are a natural by-product of applications involving physical human-robot interaction (pHRI) in unstructured environments. Robot-assisted medical ultrasound is an example of a task where simply stopping the robot upon contact detection may not be an appropriate reaction strategy. Thus, the robot should have an awareness of body contact location to properly plan force-controlled trajectories along the human body using the imaging probe. This is especially true for remote ultrasound systems where safety and manipulability are important elements to consider when operating a remote medical system through a communication network. A framework is proposed for robot contact classification using the built-in sensor data of a collaborative robot. Unlike previous studies, this classification does not discern between intended vs. unintended contact scenarios, but rather classifies what was involved in the contact event. The classifier can discern different ISO/TS 15066:2016 specific body areas along a human-model leg with 89.37% accuracy. Altogether, this contact distinction framework allows for more complex reaction strategies and tailored robot behaviour during pHRI.
Lastly, given that the success of an ultrasound task depends on the capability of the robot system to handle pHRI, pure motion control is insufficient. Force control techniques are necessary to achieve effective and adaptable behaviour of a robotic system in the unstructured ultrasound environment while also ensuring safe pHRI. While force control does not require explicit knowledge of the environment, to achieve an acceptable dynamic behaviour, the control parameters must be tuned. The third contribution proposes a simple and effective online tuning framework for force-based robotic freehand ultrasound motion control. Within the context of medical ultrasound, different human body locations have a different stiffness and will require unique tunings. Through real-world experiments with a collaborative robot, the framework tuned motion control for optimal and safe trajectories along a human leg phantom. The optimization process was able to successfully reduce the mean absolute error (MAE) of the motion contact force to 0.537N through the evolution of eight motion control parameters. Furthermore, contextual awareness through motion classification can offer a framework for pHRI optimization and safety through predictive motion behaviour with a future goal of autonomous pHRI. As such, a classification pipeline, trained using the tuning process motion data, was able to reliably classify the future force tracking quality of a motion session with an accuracy of 91.82 %
Stackelberg Meta-Learning for Strategic Guidance in Multi-Robot Trajectory Planning
Guided cooperation is a common task in many multi-agent teaming applications.
The planning of the cooperation is difficult when the leader robot has
incomplete information about the follower, and there is a need to learn,
customize, and adapt the cooperation plan online. To this end, we develop a
learning-based Stackelberg game-theoretic framework to address this challenge
to achieve optimal trajectory planning for heterogeneous robots. We first
formulate the guided trajectory planning problem as a dynamic Stackelberg game
and design the cooperation plans using open-loop Stackelberg equilibria. We
leverage meta-learning to deal with the unknown follower in the game and
propose a Stackelberg meta-learning framework to create online adaptive
trajectory guidance plans, where the leader robot learns a meta-best-response
model from a prescribed set of followers offline and then fast adapts to a
specific online trajectory guidance task using limited learning data. We use
simulations in three different scenarios to elaborate on the effectiveness of
our framework. Comparison with other learning approaches and no guidance cases
show that our framework provides a more time- and data-efficient planning
method in trajectory guidance tasks
Collaborative Robotics Strategies for Handling Non-Repetitive Micro-Drilling Tasks Characterized by Low Structural Mechanical Impedance
Mechanical micro-drilling finds widespread use in diverse applications ranging from advanced manufacturing to medical surgery. This dissertation aims to develop techniques that allow programming of robots to perform effective micro-drilling tasks. Accomplishing this goal is faced with several challenges. Micro-drills suffer from frequent breakage caused from variations in drill process parameters. Micro-drilling tasks afford extremely low feed rates and almost zero tolerance for any feed rate variations. The accompanying robot programming task is made difficult as mathematical models that capture the micro-drilling process complexities and sensitive variations in micro-drill parameters are highly difficult to obtain. Therefore, an experimental approach is adopted to identify the feasible parameter space by carrying out a systematic characterization of the tool-specimen interaction that is crucial for understanding the robotic micro-drilling process. The diameter of the hole to be drilled on a material is a primary defining factor for micro-drilling. For the purposes of this dissertation, micro-drills are defined as having a diameter less than or equal to 1 mm. The Sawyer and KUKA collaborative robots that meet the sensitive speed requirements have been chosen for this study. A regression analysis revealed a relationship between feed rate and reaction forces involved in the micro-drilling process that matched the underlying mathematical model of the tool-specimen interactions. Subsequently, this dissertation addresses the problem of destabilization in robotic micro-drilling caused by the low impedance of the collaborative robot’s cantilever structure. A semi-robotic method that combines force-controlled adaptive drill feed rate and human-assisted impedance enhancement strategy is developed to address the destabilization problem. This approach is inspired by the capability of humans to stabilize unstable dynamics while performing contact-based tasks by using selective control of arm mechanical impedance. A human-robot collaborative kinesthetic drilling mode was also developed using the selective compliance capability of the KUKA robot. Experimental results show that the Sawyer and KUKA robots can use the developed strategies to drill micro-holes of diameters up to a minimum of 0.6 mm and 0.2 mm, respectively. Finally, experiments involving drilling in different materials reveal the potential application of the collaborative robotic micro-drilling approach in composite repairs, micro-channels, dental drilling, and bone drilling
Stackelberg Game-Theoretic Trajectory Guidance for Multi-Robot Systems with Koopman Operator
Guided trajectory planning involves a leader robotic agent strategically
directing a follower robotic agent to collaboratively reach a designated
destination. However, this task becomes notably challenging when the leader
lacks complete knowledge of the follower's decision-making model. There is a
need for learning-based methods to effectively design the cooperative plan. To
this end, we develop a Stackelberg game-theoretic approach based on Koopman
operator to address the challenge. We first formulate the guided trajectory
planning problem through the lens of a dynamic Stackelberg game. We then
leverage Koopman operator theory to acquire a learning-based linear system
model that approximates the follower's feedback dynamics. Based on this learned
model, the leader devises a collision-free trajectory to guide the follower,
employing receding horizon planning. We use simulations to elaborate the
effectiveness of our approach in generating learning models that accurately
predict the follower's multi-step behavior when compared to alternative
learning techniques. Moreover, our approach successfully accomplishes the
guidance task and notably reduces the leader's planning time to nearly half
when contrasted with the model-based baseline method
Risks management and cobots. Identifying critical variables
Trabajo presentado en: 29th European Safety and Reliability Conference (ESREL), 22–26 September 2019, HannoverA collaborative robot or a "Cobot" is the name of a robot that can share a workspace with operators
in the absence of a protective fence or with only partial protection. They represent a new and expanding sector of
industrial robotics. This investigation draws from the latest international rules and safety parameters related to
work with collaborative robots. Its detailed research is motivated by the design of a collaborative industrial robot
system, hazard elimination, risk reduction, and different collaborative operations, such as power and force
limiting, collaborative operation design, and end-effector safety requirements, among others. The purpose of our
study is to analyze the most important variables that must be controlled in accordance with the desired use of the
Cobot, according to ISO / TS 15066, ISO / TR 20218-1and some other generic safety regulations on machines and
industrial robots. A series of observations and appreciations on the use of the Cobot will also be presented
Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue
Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion
- …