Suchergebnisse

Musculoskeletal disorders of the wrist are common in the meat industry. A proof of concept of a physical human-robot interaction (pHRI)-based assistive strategy for an industrial meat cutting system is demonstrated which can be transferred to an exoskeleton later. We discuss how a robot can assist a human in pHRI, specifically in the context of an industrial project i.e for the meat cutting industry. We developed an impedance control-based system that enables a KUKA LWR robot to provide assistive forces to a professional butcher while simultaneously allowing motion of the knife (tool) in all degrees of freedom. We developed two assistive strategies—a force amplification strategy and an intent prediction strategy—and integrated them into an impedance controller ; This research received funding from the French government research program Investissements d'Avenir through the UMTs ACTIA Mécarnéo-AgRobErgo and the project Exoscarne (Call P3A-ICF2A-2I2A, FranceAgriMer) and from the European Union's Horizon 2020 research and innovation programme under grant agreement nº 869855 (SoftManBot project) ; SI

The field of in-hand robot manipulation of deformable objects is an open and key issue for the next-coming robots. Developing an adaptable and agile framework for the tasks where a robot grasps and manipulates different kinds of deformable objects, is a main goal in the literature. Many research works have been proposed to control the manipulation tasks using a model of the manipulated object. Despite these techniques are precise to model the deformations, they are time consuming and, using them in real environments is almost impossible because of the large amount of objects which the robot could find. In this paper, we propose a model-independent framework to control the movements of the fingers of the hands while the robot executes manipulation tasks with deformable objects. This technique is based on tactile images which are obtained as a common interface for different tactile sensors, and uses a servo-tactile control to stabilize the grasping points, avoid sliding and adapt the contacts' configuration regarding to position and magnitude of the applied force. Tactile images are obtained using a combination of dynamic Gaussians, which allows the creation of a common representation for tactile data given by different sensors with different technologies and resolutions. The framework was tested on different manipulation tasks where the objects are deformed, and without using a model of them. ; Research supported by the Spanish Ministry of Economy, European FEDER funds, Valencia Regional Government and University of Alicante through the projects DPI2015-68087-R, PROMETEO/2013/085 and GRE 15-05. This work has been also supported by the French Government Research Program Investissements d'avenir, through the RobotEx Equipment of Excellence (ANR-10-EQPX-44) and the IMobS3 Laboratory of Excellence (ANR-10-LABX-16-01).