11:00-12:00 Harada Laboratory (Medical robotics) Hongo Campus
https://sites.google.com/g.ecc.u-tokyo.ac.jp/cdbim-medical-devices
13:00-14:00 Takahashi-Michihata Laboratory (Photon based Advanced Manufacturing Science) Hongo Campus
https://www.photon.rcast.u-tokyo.ac.jp/english/index.html
15:30-16:30 Yoshioka Laboratory (Production and processing technology) Komaba Campus
https://yoshioka-lab.iis.u-tokyo.ac.jp/index_en.html
9:30-10: 30 Kizaki Laboratory (Machine tools) Hongo Campus
https://www.hnl.t.u-tokyo.ac.jp/
10:30-11:30 Okada Laboratory (Humanoids) Hongo Campus
http://www.jsk.t.u-tokyo.ac.jp/
12:00-12:45 Lunch (Exhibition Room, 2nd floor, Eng. Bld. No.2)
<Hybrid: Open to the general public>
Abstract: Robots in the biomedical field must handle a variety of tasks involving living organisms and biological tissues, which are natural objects with inherent variability. No two are alike, and many are microscopic, posing significant challenges. Robots need both the intelligence to manage the uncertainty of these biological variations and the precision to perform delicate operations, making interdisciplinary research crucial. This symposium will feature talks from diverse fields, focusing on the core technologies of robots and precision machinery. Additionally, it will highlight a Moonshot project that leverages AI and robotics to advance scientific exploration.
Abstract: The reliability and performance of machines and robotic systems are crucial, particularly in safety-critical and harsh environments such as autonomous robotic surgery and industrial robotics with contact applications. Limited understanding of system physical characteristics, including thermo-kinematic, quasi-static, and dynamic stiffness, as well as their spatial and temporal variations, poses a barrier to autonomous application. The presentation will showcase results from past and ongoing projects focusing on identifying sources of variation and will exemplify methods and tools for calibration.
Abstract: In recent years, flexibility in production systems has been required to meet society's demands, which is moving from mass production to mass customization. The application of robotic systems is an effective solution for realizing new-generation flexible production systems. The presentation mainly introduces our research on the realization of re-configurable production systems by using industrial robots and related technologies.
Abstract: Robust and accurate compensation thermal deviation of machine tools is essential to manufacture precise biomedical components. In previous studies, uncertainty of the measurement and model itself were not considered, which made the prediction model of thermal deviation less reliable. In our study, the uncertainty caused by thermal phenomena was omitted by increasing the number of temperature sensors drastically. The large-scale temperature sensors interconnected in series (LATSIS) was proposed which enabled to attach several hundreds of temeprature sensors on a signle machine tool easily. The accuracy and the robustness of the prediction of thermal deviation with LATSIS is discussed as well as the placement strategy of large number of sensors for minimizing the measurement uncertainty.
Abstract: Recently many surgical robots are widely utilized in various surgical specialties, and it makes surgeries more efficient, stable, accurate and ergonomic. But facts about surgical safety show that there is still room for improvement about mortality rate, complications, and adverse events. We believe key to advancement is augmenting both hard skill and soft skill by technology. In this talk, we will introduce research works in Sony, Microsurgery robot enhancing surgeon’s dexterity to perform demanding micro surgical tasks and Surgical simulator reproducing authentic physical surgical interaction in virtual space for training.
Abstract: GEMPAK: A Robotic System Pioneering Autonomous Experiments in Space, JAXA Kibō, developed by JAXA, is the Japanese science module aboard the International Space Station (ISS). To enable autonomous scientific experiments with minimal astronaut intervention, JAXA has been developing a robotic system called GEMPAK, designed to support various space-based experiments. Initially focusing on rodent experiments in orbit, GEMPAK will be tele-operated from the ground, with plans to gradually enhance its autonomy. The primary challenges involve the uncertainty in robot and object behavior under microgravity conditions, where human expertise may not suffice, necessitating advanced AI for automation.
Abstract: Diabetic foot ulcers (DFU) affect a quarter of people with diabetes, costing the NHS £1 billion annually. Our team, led by Prof Andy Weightman at The University of Manchester aimed to address the issue by co-designing, with patients, the self-managed use of smart shoe insoles. The intention was for the insoles to identify early signs of ulceration through the use of normal pressure, shear pressure and temperature. Furthermore, for soft-robotic actuators in the insole to use the sensor data to adjust their shape and normalise the plantar tissue loading. In this project, we developed a sensing system that was able to measure the full stress state of the foot during walking in people living with diabetes and without, which included measuring shear stress, which has not been measured in previous studies in this scale. This led to further understanding of the mechanisms that may lead to the development of DFU. Through the development of these sensing insoles, we were then able to determine methods of prevention of DFU. These point to actively changing the loading properties of the foot, which we have started to look at by developing pneumatic based soft robotic actuating insoles. Future work will be to combine these systems together to produce a single closed-loop smart insole system for the prevention of DFU.
Abstract: Traditionally, robots have primarily been employed in tasks that do not require continuous interaction with the environment, such as material handling and painting. However, the articulated robot flexibility, adaptability, affordability, and large workspace make it attractive for a wide range of contact applications where the robot must consistently interact with the environment. The inherent low structural stiffness of articulated robots can lead to significant deformation under external loads, which, in turn, affects the accuracy of the end-effector's positioning. Therefore, improving accuracy is a crucial factor in promoting the widespread adoption of robotic systems in high-precision contact applications. This presentation introduces a quasi-static perspective of robot accuracy, a proposed approach designed to better emulate various contact applications and understand the combined effects of position, load, and motion on the robot's positioning accuracy.
Abstract: This talk presents the design methodology and principles employed in developing end-effectors for robotic systems tailored for biomedical applications, with a focus on manipulation of biological samples. The presentation highlights precision design principles, particularly emphasizing "structure" and "kinematic/semi-kinematic design”. By adhering to the 11 precision design principles for machines and instruments, the presentation will discuss the complexities of robotic end-effector design, aiming to achieve precise grasping and cutting of biological samples. Moreover, the integration of mechanisms, material choice, meticulous structure and kinematic optimization, and system reliability in robotic systems will be discussed with the help of a case study conducted at the University of Tokyo.
Abstract: This talk presents our progress on kinematic control with model-based collision constraints for millimeter-scale manipulation. Obtaining accurate kinematic model parameters is often challenging, as traditional calibration methods, online or offline, require large tracking systems or mounted markers on effector. As a proof-of-concept, we propose using U-Net for partial pose measurement combined with adaptive-constrained kinematic control. In a bi-manual setup with a robot-held microscopic camera, we demonstrated improved tracking and constraint accuracy, keeping a robot-held drill tip within the camera's view.
Abstract: This talk presents our progress in building a shared virtual laboratory between research groups at UTokyo and KTH for collaborative robotics research. We have developed a digital twin of industrial robots at KTH, implemented a kinematic controller, and tested teleoperation at KTH of the robotic system at UTokyo. The project is now expanding with enhanced digital twin capabilities and virtual reality integration, enabling real-time interaction with robotic systems. We will discuss the latest advancements and explore how this metaverse like virtual lab can facilitate seamless global collaboration and innovation in robotics.
Abstract: Biological specimens exhibit significant variations in size and shape, challenging autonomous robotic manipulation. We focus on the mouse skull window creation task to illustrate these challenges. The study introduces a microscopic stereo camera system (MSCS) enhanced by the linear model for depth perception. Alongside this, a precise registration scheme is developed for the partially exposed mouse cranial surface, employing a CNN-based constrained and colorized registration strategy. These methods are integrated with the MSCS for robotic micromanipulation tasks. The MSCS demonstrated a high precision of 0.10 mm ± 0.02 mm measured in a step height experiment and real-time performance of 30 FPS in 3D reconstruction. The registration scheme proved its precision, with a translational error of 1.13 mm ± 0.31 mm and a rotational error of 3.38° ± 0.89° tested on 105 continuous frames with an average speed of 1.60 FPS. This study presents the application of a MSCS and a novel registration scheme in enhancing the precision and accuracy of robotic micromanipulation in scientific and surgical settings. The innovations presented here offer automation methodology in handling the challenges of microscopic manipulation, paving the way for more accurate, efficient, and less invasive procedures in various fields of microsurgery and scientific research.
Monocular Estimation of Suture Needle Pose Utilizing Simulator-Generated Synthetic Data
Yifan Wang (PhD Student, UTokyo)
Abstract: Deep-learning-based visual feedback has been applied in the field of surgical robotics to enhance the autonomy, efficiency, and accuracy of robotic systems. However, a major challenge is the scarcity of large-scale medical image datasets required for effective model training. To address this, our lab has developed medical robotic simulators capable of generating synthetic datasets rapidly and accurately, reducing the workload associated with manual annotation. This presentation will demonstrate how synthetic data is used to train a convolutional neural network (CNN) to predict the keypoints of a suture needle, which can then be utilized to estimate its 3D orientation from a single image. The framework of this work has the potential to enable robotic systems to autonomously manipulate the suture needle.