5 research outputs found

    Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation

    Full text link
    Vision-based tactile sensors have gained extensive attention in the robotics community. The sensors are highly expected to be capable of extracting contact information i.e. haptic information during in-hand manipulation. This nature of tactile sensors makes them a perfect match for haptic feedback applications. In this paper, we propose a contact force estimation method using the vision-based tactile sensor DIGIT, and apply it to a position-force teleoperation architecture for force feedback. The force estimation is done by building a depth map for DIGIT gel surface deformation measurement and applying a regression algorithm on estimated depth data and ground truth force data to get the depth-force relationship. The experiment is performed by constructing a grasping force feedback system with a haptic device as a leader robot and a parallel robot gripper as a follower robot, where the DIGIT sensor is attached to the tip of the robot gripper to estimate the contact force. The preliminary results show the capability of using the low-cost vision-based sensor for force feedback applications.Comment: IEEE CBS 202

    A Review on Tactile Displays for Conventional Laparoscopic Surgery

    No full text
    Laparoscopic surgery (LS) is a minimally invasive technique that offers many advantages over traditional open surgery: it reduces trauma, scarring, and shortens recovery time. However, an important limitation is the loss of tactile sensations. Although some progress has been made in robotic-assisted minimally invasive surgery (RMIS) setups, RMIS is still not widely accessible. This review aims to identify which tactile display technologies have been proposed and experimentally validated for the restoration of tactile sensations during conventional laparoscopic surgical tasks. We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We identified relevant articles published over the past 10 years through a search on Web of science, Scopus, IEEE Xplore Digital, and PubMed repositories. A total of 143 articles met the inclusion criteria and 24 were included in the final review. From the reviewed articles, we classified the proposed tactile displays into two categories based on the use of skin contact: (i) skin tactile displays, which include vibrotactile, skin-indentation, and grip-feedback devices, and (ii) non-contact tactile displays based on visualization tools. This survey aims to contribute to further research in the area of tactile displays for laparoscopic surgery by providing a better understanding of the current state of the art and identifying the remaining challenges

    Toward Autonomous Robotic Minimally Invasive Surgery: A Hybrid Framework Combining Task-Motion Planning and Dynamic Behavior Trees

    No full text
    The growing need for high levels of autonomy in Autonomous Robotic Surgery Systems (ARSS) calls for innovative approaches to reduce surgeons’ cognitive load, optimize hospital workflows, and ensure efficient task-level reasoning and adaptation during execution. This paper presents a novel hybrid framework that synergistically combines Task-Motion Planning and Dynamic Behavior Trees for ARSS in Minimally Invasive Surgery. Our approach is designed to address the challenges of coordinating multiple surgical tools within a small workspace, thereby making complex surgical tasks like multi-throw suturing feasible and efficient. Through an extensive evaluation in simulation across diverse initial conditions and noise scenarios, the proposed method demonstrates improved success rates, reduced execution times, and fewer regrasps compared to standalone approaches. Furthermore, it showcases robustness under increased noise conditions. By applying our framework to a complex multi-throw suturing task, we illustrate its capability to seamlessly handle comprehensive suturing tasks, including needle picking, insertion, extraction, and the handover of the needle between Patient Side Manipulators. The results suggest that our hybrid approach not only enhances ARSS autonomy but also adapts effectively to unexpected environmental changes, laying the groundwork for its potential applicability in real-world surgical robotics

    Optimization-Based Constrained Trajectory Generation for Robot-Assisted Stitching in Endonasal Surgery

    No full text
    The reduced workspace in endonasal endoscopic surgery (EES) hinders the execution of complex surgical tasks such as suturing. Typically, surgeons need to manipulate non-dexterous long surgical instruments with an endoscopic view that makes it difficult to estimate the distances and angles required for precise suturing motion. Recently, robot-assisted surgical systems have been used in laparoscopic surgery with promising results. Although robotic systems can provide enhanced dexterity, robot-assisted suturing is still highly challenging. In this paper, we propose a robot-assisted stitching method based on an online optimization-based trajectory generation for curved needle stitching and a constrained motion planning framework to ensure safe surgical instrument motion. The needle trajectory is generated online by using a sequential convex optimization algorithm subject to stitching kinematic constraints. The constrained motion planner is designed to reduce surrounding damages to the nasal cavity by setting a remote center of motion over the nostril. A dual concurrent inverse kinematics (IK) solver is proposed to achieve convergence of the solution and optimal time execution, in which two constrained IK methods are performed simultaneously; a task-priority based IK and a nonlinear optimization-based IK. We evaluate the performance of the proposed method in a stitching experiment with our surgical robotic system in a robot-assisted mode and an autonomous mode in comparison to the use of a conventional surgical tool. Our results demonstrate a noticeable improvement in the stitching success ratio in the robot-assisted mode and the shortest completion time for the autonomous mode. In addition, the force interaction with the tissue was highly reduced when using the robotic system
    corecore