Occlusion-Robust Autonomous Robotic Manipulation of Human Soft Tissues With 3-D Surface Feedback

Abstract

Robotic manipulation of 3D soft objects remains challenging in the industrial and medical fields. Various methods based on mechanical modelling, data-driven approaches or explicit feature tracking have been proposed. A unifying disadvantage of these methods is the high computational cost of simultaneous imaging processing, identification of mechanical properties, and motion planning, leading to a need for less computationally intensive methods. We propose a method for autonomous robotic manipulation with 3D surface feedback to solve these issues. First, we produce a deformation model of the manipulated object, which estimates the robots' movements by monitoring the displacement of surface points surrounding the manipulators. Then, we develop a 6-degree-of-freedom velocity controller to manipulate the grasped object to achieve a desired shape. We validate our approach through comparative simulations with existing methods and experiments using phantom and cadaveric soft tissues with the da Vinci Research Kit. The results demonstrate the robustness of the technique to occlusions and various materials. Compared to state-of-the-art linear and data-driven methods, our approach is more precise by 46.5% and 15.9% and saves 55.2% and 25.7% manipulation time, respectively.Index Terms-Shape control, dual arm manipulation, robotic manipulation of soft objects I. INTRODUCTIONR OBOTIC manipulation of soft, deformable objects is a common practice in industry, from fabric folding to food packaging [1], [2], [3], [4], [5], with similar problems observed in medical scenarios. Despite recent progress in the robotic manipulation of deformable linear and planar objects, such as ropes and clothing items, the shape control of 3D objects is still a challenge.In robotic-assisted minimally invasive surgery (RAMIS) [6], soft tissues within the abdomen are manipulated with the teleoperated end-effectors of a surgical robot [7]. Recently, the research focus in this area has trended towards