A multi-robot collaboration system can complete more complex tasks than a single robot system. Ensuring the calibration accuracy between robots in the system is a prerequisite for the effective inter-robot cooperation. This paper presents a dual-robot system for orthopedic surgeries, where the relationships between hand-eye, flange-tool, and robot-robot need to be calibrated. This calibration problem can be summarized to the solution of the matrix equation of AXB=YCZ. A combined solution is proposed to solve the unknown parameters in the equation of AXB=YCZ, which consists of the dual quaternion closed-form method and the iterative method based on Levenberg–Marquardt (LM) algorithm. The closed-form method is used to quickly obtain the initial value for the iterative method so as to increase the convergence speed and calibration accuracy of the iterative method. Simulation and experimental analyses are carried out to verify the accuracy and effectiveness of the proposed method.

Intraoperative optical navigation is widely utilized in robotic surgery systems. Typically, the observation pose of the optical tracking system (OTS) is manually adjusted and then fixed throughout the surgery. However, fixed OTS suffers from limited measurement volume (MV) and visual interferences, making consistent navigation challenging in clinics. In this paper, an operation-navigation dual-robot collaborative system is proposed for orthopedic surgeries. An extra navigation robot is introduced to actively adjust the observation pose of the OTS. A collaborative preoperative planning method is proposed for this dual-robot system, including osteotomy path planning of the operation robot and collaborative planning of the navigation robot. Firstly, osteotomy paths of the operation robot are generated according to the surgery regulations and the geometric features of the vertebral foramen. Secondly, based on the generated osteotomy paths, the collaborative planning of the navigation robot is formulated into a multi-objective optimization problem to find the optimal poses of the OTS for each osteotomy plane. Compared with fixed OTS, active navigation is capable of keeping all the targets within the MV of the OTS throughout the surgery. Semi-laminectomy on a human spine phantom is adopted as an example to experimentally evaluate the effectiveness of the proposed method. Note to Practitioners —As the demand for robot-assisted surgery is increasing, the precision of operation has become one of the key safety requirements. Preoperative planning provides guidance for the surgeon, and intraoperative navigation monitor the status of the lesion and the surgical tool in real-time. In conventional intraoperative optical navigation, the OTS is manually adjusted and remains stationary. However, the limited MV and the visual interferences introduce risks and uncertainties to the surgical system. In order to address the limitations of fixed OTS, an operation-navigation dual-robot collaborative system is proposed for orthopedic surgeries, which is composed of a surgical operation module and an active navigation module. The navigation robot is used to actively adjust the pose of the OTS. A collaborative preoperative planning for the operation-navigation dual-robot orthopedic surgery system is proposed in this paper. The effectiveness of the proposed method is verified on a human spine phantom. Experimental results show that the active navigation provides more freedom to the overall system by freely adjusting the OTS, which ensures the stability of the surgical navigation. In future work, efforts will be directed toward the identification and avoidance of the obstacle.

Optical tracking system (OTS), an essential component of robot-assisted surgery, measures the position and orientation of the surgical tools during surgery operations. OTS has proven to be a reliable intra-operative navigation method in clinical applications. However, OTS suffers from the vision occlusion where obstacles block the vision of the position sensors of the OTS. To tackle with this problem, we propose an active navigation system which can automatically moves the OTS so as to avoid the occlusion and meanwhile maintain the tracking accuracy. The active navigation system is composed of a multi-DOF robot, an optical tracker and an RGB-D camera. The accuracy of OTS is influenced by several factors, such as working distance and relative orientation of the tracked tool. Since in the active navigation system, the OTS moves during navigation, the impact of the movement of OTS on its accuracy is investigated. The corresponding experiments are conducted, and the results are analyzed. Subsequently, an occlusion avoidance strategy is developed to control the OTS to not only avoid the obstacles but also keep the accuracy degradation acceptable. Ultimately, the occlusion avoidance experiment is conducted to verify the proposed strategy. The experimental results demonstrate the effectiveness of the proposed active navigation system.

Intraoperative optical tracking system (OTS) suffers from the visual occlusion problem when an obstacle blocks the visual cone (VC) of the OTS. In this paper, angle and distance margins are proposed to quantify the degree of danger of an obstacle based on its spatial relationship to the VCs of the OTS. Based on this mathematical modeling, an active navigation system is proposed, where the navigation robot is used to adjust the pose of the OTS before occlusion occurs. Circular and translational trajectories are proposed as basic adjusting trajectories for the OTS. A dual-step optimization is then established to find the optimal observation pose of the OTS and plan an occlusion-free adjusting trajectory for the navigation robot. Finally, simulations and experiments are conducted to validate the effectiveness of the proposed method. The results demonstrate that the proposed method effectively keeps the VCs of the OTS away from the moving path of the obstacle, and thus maintaining consistent navigation. This active navigation method is promising for the safe operations of surgical systems employing optical navigation.

In robotic orthopedic surgery, the optical tracking system (OTS) is typically placed in a fixed location. In surgery, the OTS’s line of sight is likely to be blocked. This will interrupt the navigation and affect surgical safety. To solve this occlusion problem, an RGB-D camera is used to detect possible occluders and a navigation robot is utilized to actively adjust the OTS viewpoint before occlusion occurs. To guarantee the applicability, the occluder is enveloped using a convex polytope, and a two-phase optimization method is proposed based on duality of convex optimization. The effectiveness of the proposed method is verified via simulations and experiments. Experimental results show that the proposed method can avoid occlusion between the OTS and the occluder, and the targets are located near the center of the measurement volume. This active navigation guarantees the continuity of intraoperative navigation, and thus helps to improve the safety in robotic orthopedic surgery.

Optical navigation is the mainstream technology used in intraoperative navigation for the orthopedic surgical robot. The information loss problem in optical navigation system (OTS) seriously affects the surgical process. Different from the conventional orthopedic surgical robot systems, we propose to use an additional navigation robot to adjust the viewpoint of the OTS. In this navigation-operation dual-robot collaborative robotic system for orthopedic surgery (NOR2CORS), a comprehensive range of functions are realized, including CT image segmentation, path planning, intraoperative operation, and active navigation. In this paper, pedicle screw placement is adopted as an example to assess the effectiveness and performance of the NOR2CORS. An assessment criterion is also proposed to assess the accuracy of pedicle screw placement based on the widely-used Gertzbein and Robbins classification. Experiments are conducted on a human spine model (24 pedicles) and ex-vivo porcine spine (10 pedicles). According to the proposed assessment criterion, 96% pedicles on human spine model can be classified as grade A and 4% grade B, with 67% of them as grade A2 and above. In the ex-vivo porcine spine experiment, all pedicle screw placements can be classified as grade A, with 80% of them as grade A2 and above. In the surgical process, all positioning targets can be observed without any interruption in navigation. These results demonstrated the efficiency and accuracy of the NOR2CORS.