Real-time active constraint generation and enforcement for surgical tools using 3D detection and localisation network.

Introduction: Collaborative robots, designed to work alongside humans for manipulating end-effectors, greatly benefit from the implementation of active constraints. This process comprises the definition of a boundary, followed by the enforcement of some control algorithm when the robot tooltip interacts with the generated boundary. Contact with the constraint boundary is communicated to the human operator through various potential forms of feedback. In fields like surgical robotics, where patient safety is paramount, implementing active constraints can prevent the robot from interacting with portions of the patient anatomy that shouldn't be operated on. Despite improvements in orthopaedic surgical robots, however, there exists a gap between bulky systems with haptic feedback capabilities and miniaturised systems that only allow for boundary control, where interaction with the active constraint boundary interrupts robot functions. Generally, active constraint generation relies on optical tracking systems and preoperative imaging techniques. Methods: This paper presents a refined version of the Signature Robot, a three degrees-of-freedom, hands-on collaborative system for orthopaedic surgery. Additionally, it presents a method for generating and enforcing active constraints "on-the-fly" using our previously introduced monocular, RGB, camera-based network, SimPS-Net. The network was deployed in real-time for the purpose of boundary definition. This boundary was subsequently used for constraint enforcement testing. The robot was utilised to test two different active constraints: a safe region and a restricted region. Results: The network success rate, defined as the ratio of correct over total object localisation results, was calculated to be 54.7% ± 5.2%. In the safe region case, haptic feedback resisted tooltip manipulation beyond the active constraint boundary, with a mean distance from the boundary of 2.70 mm ± 0.37 mm and a mean exit duration of 0.76 s ± 0.11 s. For the restricted-zone constraint, the operator was successfully prevented from penetrating the boundary in 100% of attempts. Discussion: This paper showcases the viability of the proposed robotic platform and presents promising results of a versatile constraint generation and enforcement pipeline.

Dimensionality Reduction in Controlling Articulated Snake Robot for Endoscopy Under Dynamic Active Constraints.

This paper presents a real-time control framework for a snake robot with hyper-kinematic redundancy under dynamic active constraints for minimally invasive surgery. A proximity query (PQ) formulation is proposed to compute the deviation of the robot motion from predefined anatomical constraints. The proposed method is generic and can be applied to any snake robot represented as a set of control vertices. The proposed PQ formulation is implemented on a graphic processing unit, allowing for fast updates over 1 kHz. We also demonstrate that the robot joint space can be characterized into lower dimensional space for smooth articulation. A novel motion parameterization scheme in polar coordinates is proposed to describe the transition of motion, thus allowing for direct manual control of the robot using standard interface devices with limited degrees of freedom. Under the proposed framework, the correct alignment between the visual and motor axes is ensured, and haptic guidance is provided to prevent excessive force applied to the tissue by the robot body. A resistance force is further incorporated to enhance smooth pursuit movement matched to the dynamic response and actuation limit of the robot. To demonstrate the practical value of the proposed platform with enhanced ergonomic control, detailed quantitative performance evaluation was conducted on a group of subjects performing simulated intraluminal and intracavity endoscopic tasks.

Stereoscopic Near-Infrared Fluorescence Imaging: A Proof of Concept Toward Real-Time Depth Perception in Surgical Robotics.

The increasing use of surgical robotics has provoked the necessity for new medical imaging methods. Many assistive surgical robotic systems influence the surgeon's movements based on a model of constraints and boundaries driven by anatomy. This study aims to demonstrate that Near-Infrared Fluorescence (NIRF) imaging could be applied in surgical applications to provide subsurface mapping of capillaries beneath soft tissue as a method for imaging active constraints. The manufacture of a system for imaging in the near-infrared wavelength range is presented, followed by a description of computational methods for stereo-post-processing and data acquisition and testing used to demonstrate that the proposed methods are viable. The results demonstrate that it is possible to use NIRF for the imaging of a capillary submersed up to 11 mm below a soft tissue phantom, over a range of angles from 0° through 45°. Phantom depth has been measured to an accuracy of ±3 mm and phantom angle to a constant accuracy of ±1.6°. These findings suggest that NIRF could be used for the next generation of medical imaging in surgical robotics and provide a basis for future research into real-time depth perception in the mapping of active constraints.

High-accuracy drilling with an image guided light weight robot: autonomous versus intuitive feed control.

PURPOSE: Assistance of robotic systems in the operating room promises higher accuracy and, hence, demanding surgical interventions become realisable (e.g. the direct cochlear access). Additionally, an intuitive user interface is crucial for the use of robots in surgery. Torque sensors in the joints can be employed for intuitive interaction concepts. Regarding the accuracy, they lead to a lower structural stiffness and, thus, to an additional error source. The aim of this contribution is to examine, if an accuracy needed for demanding interventions can be achieved by such a system or not. METHODS: Feasible accuracy results of the robot-assisted process depend on each work-flow step. This work focuses on the determination of the tool coordinate frame. A method for drill axis definition is implemented and analysed. Furthermore, a concept of admittance feed control is developed. This allows the user to control feeding along the planned path by applying a force to the robots structure. The accuracy is researched by drilling experiments with a PMMA phantom and artificial bone blocks. RESULTS: The described drill axis estimation process results in a high angular repeatability ([Formula: see text]). In the first set of drilling results, an accuracy of [Formula: see text] at entrance and [Formula: see text] at target point excluding imaging was achieved. With admittance feed control an accuracy of [Formula: see text] at target point was realised. In a third set twelve holes were drilled in artificial temporal bone phantoms including imaging. In this set-up an error of [Formula: see text] and [Formula: see text] was achieved. CONCLUSION: The results of conducted experiments show that accuracy requirements for demanding procedures such as the direct cochlear access can be fulfilled with compliant systems. Furthermore, it was shown that with the presented admittance feed control an accuracy of less then [Formula: see text] is achievable.