Constraint of musculoskeletal tissue and path planning of robot‐assisted fracture reduction with collision avoidance

Abstract

Background: For the robot-assisted fracture reduction, due to the complex fracture musculoskeletal environment, it is necessary to consider the influence of soft tissue traction on preoperative reduction path planning.Method: An improved 3D A* algorithm is adopted to plan the fracture reduction path. The distal fragment point clouds are updated to avoid the collision, and the end point coordinates of the muscles are updated to calculate muscular lengths during the path search.Results: 3D reduction path of long-bone fracture is planned, effectively avoiding the fracture fragments collision and ensuring the length of the corresponding muscle is always less than the allowable maximum muscle length after elongation. Conclusion:The proposed method can effectively avoid the collision between the distal fragment and the proximal fragment during the fracture reduction, can avoid secondary injury of the muscles around the femoral bone caused by overdistraction, and effectively improve the safety of robot reduction operation.

Adaptive variable impedance position/force tracking control of fracture reduction robot

“…According to the CT scan data of the fractured bone, a 3D fracture model was established, and the fracture deviation was [ x y z α β γ ] T = [−27.66 mm 23.11 mm 13.28 mm 7.37° 2.34° 5.64°] T . The 3D A* algorithm 40 is used to plan the reduction path, and the path point is obtained. Firstly, move quickly to 20 mm along the femoral axis.…”

Autonomous path planning for robot‐assisted pelvic fracture closed reduction with collision avoidance

“…Due to the random nature of the RRT* algorithm, it resulted in low search efficiency. Therefore, Buschbaum, 16 Li, 17 and Xu 18 et al. employed the A* algorithm to search for the reduction path.…”

“…Li 15 utilised cylindrical and spherical bounding boxes to detect collisions between bones, which only applies to simple bone morphology. In addition, Xu 18 proposed a discrete intersection test, which identifies whether the point cloud data of distal and proximal fragments intersect to determine whether a collision exists. This method applies to the collision detection of different morphological fragments.…”

“…This method applies to the collision detection of different morphological fragments. Therefore, we combined the technique of Xu 18 with the Octree spatial division algorithm to detect collisions between pelvic fragments while using the bounding box technique to detect collisions between dislocated bones and pelvic organs.…”

“…Due to the random nature of the RRT* algorithm, it resulted in low search efficiency. Therefore, Buschbaum, 16 Li, 17 and Xu 18 et al employed the A* algorithm to search for the reduction path. Given the high frequency of application of the A* algorithm in the PLFCR path planning and its efficient path search performance, this paper uses the A* algorithm to plan the RPFCR path.…”