Interaction Control of a Robotic Manipulator With the Surface of Deformable Object

• Published in: IEEE transactions on robotics 2023-04, Vol.39 (2), p.1321-1340
• Main Authors: Dometios, Athanasios C., Tzafestas, Costas S.
• Format: Article
• Language: English
• Subjects: Active stiffness control; Contact force; Controllability; Deformable models; Deformation; Finite element method; Formability; Interactive control; manipulation of deformable object; manipulation planning; Manipulators; Motion planning; Parameterization; Planning; Preprocessing; reactive and sensor- based planning; Robot arms; Robot control; Robot dynamics; Robot kinematics; Robotics; Robots; Stiffness; Strain; Task analysis; Tracking; Trajectory planning; Visualization
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2022.3226143

Robotic manipulation of deformable objects has drawn the attention of researchers over the past few years and is associated with a large spectrum of new application perspectives. In this article, we present an efficient integrated motion planning framework to effectively and accurately control a robotic manipulator executing interactive tasks on the surface of a deformable object. The proposed interactive motion planning framework is based on a mesh representation of the object, integrating three efficient preprocessing algorithmic steps, including visual object segmentation, finite element method deformation tracking, and local mesh parameterization. The use of barycentric coordinates, defined on the mesh triangles, enables the establishment of bijective transformations between the deformable part of an object surface and its planar (static and dynamic) parameterized mapping. By merging these spatial transformations with the preprocessing steps, in combination with an active stiffness scheme for robot manipulator control, we are able to achieve accurate and reactive motion planning of interactive trajectories, even under large and persistent visual occlusions (such as due to the presence of the robot in the visual scene). An extensive experimental evaluation study is presented, involving a robotic manipulator in interaction with a hemispherical model of controllable periodic active deformation, which permits precise ground truth derivation. Motion planning accuracy is evaluated in comparison with our previous direct vision-based approach, showing clearly superior performance of the proposed approach under all experimental conditions. The performance of the proposed framework is also further highlighted in tasks involving physical point tracking, interactive programming by human demonstration, as well as contact force regulation.