Yili Fu

Bio: Yili Fu is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Computer science & Artificial intelligence. The author has an hindex of 13, co-authored 71 publications receiving 748 citations.

Master-slave control strategy for abdominal minimally invasive surgery robotic system

Abstract: According to characteristics of abdominal minimally invasive robotic surgical tasks, based on performant industrial computer platform, an extended multifunctional hardware communicates with PCI-bus is designed, a master-slave control system is studied. In order to solve the problem of low responsivity caused by traditional inverse kinematics transformation method, a algorithm based on equivalent differential transformation suitable for real-time master-slave surgical robot control is put forward, and the accumulated error of the algorithm is eliminated by feedback mechanism. A fast trajectory planning method efficient in real-time master-slave surgical robot control is put forward to replace traditional trajectory prediction and off-line calculation. Finally, in order to avoid the impact on the accuracy of the system coursed by hand-trembling of operators, a digital filter is designed to help filtering the master manipulator signal.

Stable jump control for the wheel-legged robot based on TMS-DIP model

Abstract: Purpose The purpose of this paper is to propose a novel jump control method based on Two Mass Spring Damp Inverted Pendulum (TMS-DIP) model, which makes the third generation of hydraulic driven wheel-legged robot prototype (WLR-3P) achieve stable jumping. Design/methodology/approach First, according to the configuration of the WLR, a TMS-DIP model is proposed to simplify the dynamic model of the robot. Then the jumping process is divided into four stages: thrust, ascent, descent and compression, and each stage is modeled and solved independently based on TMS-DIP model. Through WLR-3P kinematics, the trajectory of the upper and lower centroids of the TMS-DIP model can be mapped to the joint space of the robot. The corresponding control strategies are proposed for jumping height, landing buffer, jumping attitude and robotic balance, so as to realize the stable jump control of the WLR. Findings The TMS-DIP model proposed in this paper can simplify the WLR dynamic model and provide a simple and effective tool for the jumping trajectory planning of the robot. The proposed approach is suitable for hydraulic WLR jumping control. The performance of the proposed wheel-legged jump method was verified by experiments on WLR-3P. Originality/value This work provides an effective model (TMS-DIP) for the jump control of WLR-3P. The results showed that the number of landing shock (twice) and the pitch angle fluctuation range (0.44 rad) of center of mass of the jump control method based on TMS-DIP model are smaller than those based on spring-loaded inverted pendulum model. Therefore, the TMS-DIP model makes the jumping process of WLR more stable and gentler.

Extended high-gain observer based adaptive control of flexible-joint surgical robot

Abstract: Due to the surgical robot flexible joint state vectors are not all measurable, in order to reduce the effect of the modeling errors and nonlinear factors of the flexible-joint manipulator caused by gravity and friction, an extended high-gain observer (EHGO) based adaptive control algorithm is designed to perform the position tracking control of the flexible-joint manipulator. First, gravity and friction are fed forward to reduce the nonlinearity of the robotic manipulator. Secondly, an extended high gain observer is used to observe the angular velocity of the joint and correct compensation errors of gravity and friction in real time. Finally, EHGO based adaptive controller is used to eliminate the inertia parameter measurement errors of the dynamic model, and to achieve high precision position tracking control. Simulation experiments show that the proposed control method can improve the position tracking accuracy of the flexible-joint manipulator and restrain the flexible-joint vibration obviously, and thus verifies that the designed controller can meet the requirements of accurate tracking control of the surgical robot.

A novel Stereo-IMU system based on accurate pose parameterization of two-wheeled inverted pendulum (TWIP) robot in localization and mapping

Abstract: Purpose This paper aims to propose a method to solve the problem of localization and mapping of a two-wheeled inverted pendulum (TWIP) robot on the ground using the Stereo–inertial measurement unit (IMU) system. This method reparametrizes the pose according to the motion characteristics of TWIP and considers the impact of uneven ground on vision and IMU, which is more adaptable to the real environment. Design/methodology/approach When TWIP moves, it is constrained by the ground and swings back and forth to maintain balance. Therefore, the authors parameterize the robot pose as SE(2) pose plus pitch according to the motion characteristics of TWIP. However, the authors do not omit disturbances in other directions but perform error modeling, which is integrated into the visual constraints and IMU pre-integration constraints as an error term. Finally, the authors analyze the influence of the error term on the vision and IMU constraints during the optimization process. Compared to traditional algorithms, the algorithm is simpler and better adapt to the real environment. Findings The results of indoor and outdoor experiments show that, for the TWIP robot, the method has better positioning accuracy and robustness compared with the state-of-the-art. Originality/value The algorithm in this paper is proposed for the localization and mapping of a TWIP robot. Different from the traditional positioning method on SE(3), this paper parameterizes the robot pose as SE(2) pose plus pitch according to the motion of TWIP and the motion disturbances in other directions are integrated into visual constraints and IMU pre-integration constraints as error terms, which simplifies the optimization parameters, better adapts to the real environment and improves the accuracy of positioning.

ACAM-FoC: A Deep Neural Network Augmented From CAM-FoC to Measure the Grip Force of Mass-Produced Elongated Surgical Instruments

Abstract: Learning-based grip force measurement methods in robot-assisted minimally invasive surgery (RAMIS) outperforms the traditional model-based methods and avoids the application issues of sensor-based approaches. However, few studies have investigated the problem of grip force measurement in mass-produced surgical instruments. This letter takes the difference in motion hysteresis and mechanism friction among mass-produced surgical instruments into account, and proposes a novel learning-based method ACAM-FoC. ACAM-FoC is an augmentation of CAM-FoC, which is a high accuracy lightweight network proposed in our preceding research. Loss function monotonicity limitation is introduced to alleviate the negative effect of unbalance training data. Offiline experiments are conducted to verify the effectiveness and the advantages over other two existing methods. Online experiments on the self-developed surgical robot system are conducted to preliminarily realize and verify the grip force measurement and feedback in real time. The results support the importance of grip force feedback in leader-follower operation tasks.

Continuum Robots for Medical Applications: A Survey

Abstract: In this paper, we describe the state of the art in continuum robot manipulators and systems intended for application to interventional medicine. Inspired by biological trunks, tentacles, and snakes, continuum robot designs can traverse confined spaces, manipulate objects in complex environments, and conform to curvilinear paths in space. In addition, many designs offer inherent structural compliance and ease of miniaturization. After decades of pioneering research, a host of designs have now been investigated and have demonstrated capabilities beyond the scope of conventional rigid-link robots. Recently, we have seen increasing efforts aimed at leveraging these qualities to improve the frontiers of minimally invasive surgical interventions. Several concepts have now been commercialized, which are inspiring and enabling a current paradigm shift in surgical approaches toward flexible access routes, e.g., through natural orifices such as the nose. In this paper, we provide an overview of the current state of this field from the perspectives of both robotics science and medical applications. We discuss relevant research in design, modeling, control, and sensing for continuum manipulators, and we highlight how this work is being used to build robotic systems for specific surgical procedures. We provide perspective for the future by discussing current limitations, open questions, and challenges.

Ferromagnetic soft continuum robots

Abstract: Small-scale soft continuum robots capable of active steering and navigation in a remotely controllable manner hold great promise in diverse areas, particularly in medical applications. Existing continuum robots, however, are often limited to millimeter or centimeter scales due to miniaturization challenges inherent in conventional actuation mechanisms, such as pulling mechanical wires, inflating pneumatic or hydraulic chambers, or embedding rigid magnets for manipulation. In addition, the friction experienced by the continuum robots during navigation poses another challenge for their applications. Here, we present a submillimeter-scale, self-lubricating soft continuum robot with omnidirectional steering and navigating capabilities based on magnetic actuation, which are enabled by programming ferromagnetic domains in its soft body while growing hydrogel skin on its surface. The robot's body, composed of a homogeneous continuum of a soft polymer matrix with uniformly dispersed ferromagnetic microparticles, can be miniaturized below a few hundreds of micrometers in diameter, and the hydrogel skin reduces the friction by more than 10 times. We demonstrate the capability of navigating through complex and constrained environments, such as a tortuous cerebrovascular phantom with multiple aneurysms. We further demonstrate additional functionalities, such as steerable laser delivery through a functional core incorporated in the robot's body. Given their compact, self-contained actuation and intuitive manipulation, our ferromagnetic soft continuum robots may open avenues to minimally invasive robotic surgery for previously inaccessible lesions, thereby addressing challenges and unmet needs in healthcare.