This paper presents a dynamic constraint formulation to provide protective virtual fixtures of 3D anatomical structures from polygon mesh representations. The proposed approach can anisotropically limit the tool motion of surgical robots without any assumption of the local anatomical shape close to the tool. Using a bounded search strategy and Principle Directed tree, the proposed system can run efficiently at 180 Hz for a mesh object containing 989,376 triangles and 493,460 vertices. The proposed algorithm has been validated in both simulation and skull cutting experiments. The skull cutting experiment setup uses a novel piezoelectric bone cutting tool designed for the da Vinci research kit. The result shows that the virtual fixture assisted teleoperation has statistically significant improvements in the cutting path accuracy and penetration depth control. The code has been made publicly available at https://github.com/mli0603/PolygonMeshVirtualFixture.
The University of Tokyo（东京大学）；Kitasato University Hospital（北里大学医院）
The limited workspace in pediatric endoscopic surgery makes surgical suturing one of the most difficult tasks. During suturing, surgeons have to prevent collisions between tools and also collisions with the surrounding tissues. Surgical robots have been shown to be effective in adult laparoscopy, but assistance for suturing in constrained workspaces has not been yet fully explored. In this letter, we propose guidance virtual fixtures to enhance the performance and the safety of suturing while generating the required task constraints using constrained optimization and Cartesian force feedback. …
Collaborative Drill Alignment in Surgical Robotics
University of Cambridge（剑桥大学）；Control Lab, Department of Engineering（工程系控制实验室）；Department of Engineering, University of Cambridge（剑桥大学工程系）；Department of Veterinary Medicine, University of Cambridge（剑桥大学兽医学系）
the University of Tokyo（东京大学）；Federal University of Minas Gerais（米纳斯吉拉斯联邦大学）；The University of Tokyo Hospital（东京大学医院）；Johns Hopkins University（约翰斯·霍普金斯大学）
In adult laparoscopy, robot-aided surgery is a reality in thousands of operating rooms worldwide, owing to the increased dexterity provided by the robotic tools. Many robots and robot control techniques have been developed to aid in more challenging scenarios, such as pediatric surgery and microsurgery. However, the prevalence of case-specific solutions, particularly those focused on non-redundant robots, reduces the reproducibility of the initial results in more challenging scenarios. In this paper, we propose a general framework for the control of surgical robotics in constrained workspaces …
Autonomous robotic surgery requires deliberation, i.e. the ability to plan and execute a task adapting to uncertain and dynamic environments. Uncertainty in the surgical domain is mainly related to the partial pre-operative knowledge about patient-specific anatomical properties. In this paper, we introduce a logic-based framework for surgical tasks with deliberative functions of monitoring and learning. The DEliberative Framework for Robot-Assisted Surgery (DEFRAS) estimates a pre-operative patient-specific plan, and executes it while continuously measuring the applied force obtained from a bi…
Autonomy in robot-assisted surgery is essential to reduce surgeons' cognitive load and eventually improve the overall surgical outcome. A key requirement for autonomy in a safety-critical scenario as surgery lies in the generation of interpretable plans that rely on expert knowledge. Moreover, the Autonomous Robotic Surgical System (ARSS) must be able to reason on the dynamic and unpredictable anatomical environment, and quickly adapt the surgical plan in case of unexpected situations. In this paper, we present a modular Framework for Robot-Assisted Surgery (FRAS) in deformable anatomical envi…
Toward Reliable AR-Guided Surgical Navigation: Interactive Deformation Modeling with Data-Driven Biomechanics and Prompts
Department of Computer Science and Engineering, The Chinese University of Hong Kong, HKSAR, China（计算机科学与工程系，香港中文大学（深圳））；Center of Smart Health, School of Nursing, The Hong Kong Polytechnic University, HKSAR, China（智能健康中心，香港理工大学）；Department of Hepatobiliary Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China（肝胆外科部，南方医科大学第三附属医院）
Tendon-driven robots, a type of continuum robot, have the potential to reduce the invasiveness of surgery by enabling access to difficult-to-reach anatomical targets. In the future, the automation of surgical tasks for these robots may help reduce surgeon strain in the face of a rapidly growing population. However, directly encoding surgical tasks and their associated context for these robots is infeasible. In this work we take steps toward a system that is able to learn to successfully perform context-dependent surgical tasks by learning directly from a set of expert demonstrations. We presen…
Novel Ex-vivo Calf Brain Model with Integrated Sub-Skull Force Sensors to Access Simulated Neurosurgical Procedures
McGill University（麦吉尔大学）；Montreal Neurological Institute and Hospital（蒙特利尔神经病学研究所与医院）；Ministry of the National Guard-Health Affairs（国民警卫队卫生部）；King Saud Bin Abdulaziz University for Health Sciences（阿卜杜勒阿齐兹国王健康科学大学）；King Abdullah International Medical Research Center（阿卜杜拉国王国际医学研究中心）；Federal University of Sao Carlos（圣卡洛斯联邦大学）
STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a new robotic system for application to intraluminal surgical procedures. Preclinical testing of STRAS has recently permitted to demonstrate major advantages of the system in comparison with classic procedures. Benchmark methods permitting to establish objective criteria for expertise need to be worked out now to effectively train surgeons on this new system in the near future. STRAS consists of three cable driven subsystems, one endoscope serving as guide, and two flexible instruments. The flexible instruments have three deg…
Fluoroscopy-Constrained Magnetic Robot Control via Zernike-Based Field Modeling and Nonlinear MPC
Laboratory for Computational Sensing and Robotics（计算感知与机器人实验室）；Johns Hopkins University（约翰霍普金斯大学）；Department of Mechanical Engineering（机械工程系）；University of Maryland（马里兰大学）；Division of Magnetic Manipulation and Particle Research（磁操控与粒子研究部）；Weinberg Medical Physics（韦因伯格医学物理）
Learning-based Hierarchical Tracheal Anatomy Understanding from Sparse Surgical Demonstration Annotations for Ultrasound Robots
The Chinese University of Hong Kong（香港中文大学）；Imperial College London（伦敦帝国学院）；Hong Kong Institute of Science and Innovation, Chinese Academy of Sciences（中国科学院香港创新研究院）；SLAI Shenzhen Loop Area Institute（深圳环域先进人工智能研究院）
ArthroCut: Autonomous Policy Learning for Robotic Bone Resection in Knee Arthroplasty
School of Biomedical Engineering, Tsinghua University（清华大学生物医学工程学院）；School of Biomedical Engineering, Shanghai Jiao Tong University（上海交通大学生物医学工程学院）；Longwood Valley MedTech
