Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new applications in the industrial, services, and healthcare sectors. However, compared to rigid object manipulation, the manipulation of deformable objects is considerably more complex, and is still an open research problem. Tackling the challenges in DOM demands breakthroughs in almost all aspects of robotics, namely hardware design, sensing, deformation modeling, planning, and control. In this article, we highlight the main challenges that arise by considering deformation and review recent advances in each sub-field. A particular focus of our paper lies in the discussions of these challenges and proposing promising directions of research.

No abstract

International audienceThis paper introduces a visual servoing scheme for humanoid walking. Though most of the existing approaches follow a perception-decision-action scheme, we close the loop so that the control is robust to model error. Our approach is based on a new reactive pattern generator which modifies, at the control level, the footsteps, the center of mass and the center of pressure trajectories for the center of mass to track a reference velocity. And, in this paper, the reference velocity is directly given by a visual servoing control law. Since, the HRP- 2 walk induces a sway motion that disturbs the regulation of the visual control law, we introduce a control law allowing convergence in the image space and taking into account this sway motion

Tethers are used to supply power and transfer data for teleoperated robots. They are known to limit the robot's workspace and could have the effect of hampering its motion. What if we could take advantage of the tether? In this paper a new visual servoing scheme for catenary shaped deformable objects is introduced in order to control the tether parametric shape by properly moving its fixation point. In most of the visual servoing approaches the target object is rigid and distant from the controlled robot. On the contrary, in this paper, the object is deformable and attached to the robot, thus its 3D shape changes while the robot is moving. The experimental system is composed of two terrestrial mobile robots of the same motion capabilities linked with a slack rope. Simulation and real experiments validate the proposed control scheme for proper tether handling.

This paper presents a method to determine the rough shape of an object. This is a step in the development of a "One Click Grasping Tool", a grasping tool of everyday-life objects for an assistant robot dedicated to elderly or disabled. The goal is to determine the quadric that approximates at best the shape of an unknown object using multi-view measurements. Non-linear optimization techniques are considered to achieve this goal. Since multiple views are necessary, an active vision process is considered in order to minimize the uncertainty on the estimated parameters and determine the next best view. Finally, results that show the validity of the approach are presented.