Surgical Robot, Path Planning, Joint Space, Riemannian Manifolds
This addresses path planning challenges for surgical robots in minimally invasive surgery, offering an incremental improvement over existing methods.
The paper tackled the problem of robotic surgery path planning under joint angle limitations and non-concave abdominal cavity surfaces by proposing a method that transforms positions into a Riemannian manifold in joint space, resulting in reduced range of joint angle movement compared to position space calculations.
Robotic surgery for minimally invasive surgery can reduce the surgeon's workload by autonomously guiding robotic forceps. Movement of the robot is restricted around a fixed insertion port. The robot often encounters angle limitations during operation. Also, the surface of the abdominal cavity is non-concave, making it computationally expensive to find the desired path.In this work, to solve these problems, we propose a method for path planning in joint space by transforming the position into a Riemannian manifold. An edge cost function is defined to search for a desired path in the joint space and reduce the range of motion of the joints. We found that the organ is mostly non-concave, making it easy to find the optimal path using gradient descent method. Experimental results demonstrated that the proposed method reduces the range of joint angle movement compared to calculations in position space.