In recent years, there has been a growing interest in robotic manipulation of deformable objects. In order to perform certain tasks, the robot must control the shape of the object while taking care not to apply excessive stresses so as not to deform it irreversibly. This is the case when extracting elasto-plastic objects in strips from an industrial reel. In order to control the mechanical stresses within the object, we propose a vision-based control scheme to minimize tension by regulating the angular velocity of a motorized reel on which they are wound. In this paper, we propose a method, based on a catenary model and visual feedback from a low-cost RGB-D camera, to estimate the tension distribution along a rubber strip. Thus, the control strategy aims to achieve a desired tension value by varying the length of the suspended portion of the manipulated strip. Simulation and experimental results validate the proposed approach for strip-like objects of various dimensions.

Robots are nowadays faced with the challenge of handling deformable objects in industrial operations. In particular, the problem of shape control, which aims at giving a specific deformation state to an object, has gained interest recently in the research community. Among the proposed solutions, approaches based on finite elements proved accurate and reliable but also complex and computationally-intensiveIn order to mitigate these drawbacks, we propose a scheme for shape control that does not require to run a real-time simulation or to solve an implicit optimization problem for computing the control outputs. It is based on a partition of the nodal coordinates that allows deriving a control law directly from tangent stiffness matrices. This formulation is also coupled with the introduction of reduced finite element models. Simulation and experimental results in the context of linear deformable object manipulation demonstrate the interest of the proposed approach.

The 3-CRS manipulator is an original parallel mechanism having 6 degrees of freedom (DOFs) with only 3 limbs. This mechanism uses a motorized cylindrical joint per limb. This new paradigm of actuation opens research fields on new families of robots that should particularly interest the parallel robotics community. According to its dimensional synthesis, this mechanism can have remarkable kinematic properties such as a large orientation workspace or reconfiguration capabilities. In this paper, we introduce this mechanism and we study its singularities by using a geometric approach. This approach simplifies considerably singularity analysis problem by considering the relative geometric configurations of three planes defined by the distal links of the limbs. Thanks to that, a reconfiguration mode of the 3-CRS, that doubles its reachable workspace, is highlighted. This property is illustrated on a physical prototype of the robot.

Finding the current pose of the end-effector of a parallel robot is a problem, since its forward geometric model generally has several solutions. Current methods to address this problem operate mainly under the assumption that the robot never changes its assembly mode nor gets close to Type 2 singularities. Nonetheless, recent works proved that a parallel robot can change its assembly mode, thanks to dedicated trajectory generation and control. Such a feature allows increasing the operational workspace of such manipulators. Hence, correctly tracking the end-effector pose while crossing Type 2 singularities is mandatory for a practical usage of this workspace enhancement method. However, on Type 2 singularities, several solutions of the forward geometric model merge, making current tracking methods ineffective. To fill this gap, we propose a two-step pose tracking methodology. First, a differential inclusion based on kinematics and dynamics is solved. Second, joint measurements are used to tighten resulting enclosures. The effectiveness of this method is discussed, thanks to experimental data gathered on a planar parallel robot.

Increasing the size of operationnal workspace is one of the main problems parallel robots are faced with. Among all the proposed solutions to that, crossing Type 2 singularities using dedicated trajectory generation and multi-model controller has a great potential. Yet, this approach is not sufficient for the robot to operate autonomously, as assembly mode detection during the motion currently requires additional redundant information. To tackle this problem, we propose an algorithm based on Interval Analysis (IA) that is able to track the end-effector of the robot even under assembly mode change. IA-based solvers for the forward kinematic problem of parallel robots are well known, but they cannot be used under assembly mode change. Compared to those classical approaches, the major modification introduced is the tracking of end-effector velocity in addition to its pose. Using this new information of velocity, the algorithm is capable to monitor the assembly mode change of the robot happening when the singularities are crossed. The behavior and the reliability of this algorithm are analyzed experimentally on a five-bar planar parallel mechanism.