A DeVice Independent programming and control framework for robotic HANDS Università di Siena Università di Pisa and Istituto Italiano di Tecnologia HANDSDVI Kick Off Meeting IIT January 2011 ID: 298609
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HANDS.DVI A DeVice-Independent programming and control framework for robotic HANDS
Università di Siena , Università di Pisa and Istituto Italiano di TecnologiaHANDS.DVI Kick Off Meeting @ IIT, January 2011 Slide2
ECHORD ECHORD (European Clearing House for Open Robotics Development) is a EU funded project aiming to strengthen the cooperation between scientific research and industry in robotics. However, finding common ground between manufacturers and the research community, especially when it comes to defining the future direction of robotics research, has proven difficult in the past. ECHORD will act as a "clearing house" to streamline successful know-how transfers. ECHORD is coordinated by
Technical University of Munich. The experiments are the ECHORD projects. Slide3
The problem
Because of their intrinsic complexity, there is not a standard approach to the control of grasping and manipulation tasks. Borrowing the terminology of software engineering, there is a need for middleware solutions for manipulation and grasping tasks to seamlessly integrate robotic hands in flexible cells. Slide4
The project’s idea The abstraction layer is based on sensorimotor synergies.Synergies with the The Hand Embodied EU project. Slide5
Sensorimotor synergies
Recent
results on the organization of the human hand in grasping and manipulation
are
the
inspiration
for this
project proposal: these results have demonstrated that, notwithstanding the complexity of the human hand,
a
few variables
are able to account for most of the variance in the patterns of human hands configuration
and movement.Slide6Slide7Slide8
(Simulations by UNIPI)Slide9
(Simulations by UNIPI)Slide10
HANDS.DVISlide11
Hands controlled with few knobsSlide12Slide13
The main pointsThe paradigmatic hand: ``A trade–off between the complexity of the human hand model accounting for the synergistic organization of the sensorimotor system and the simplicity of the models of robotic hands available on the market. ‘’Postural synergies``The paradigmatic hand will be developed to define a basis of synergies that will allow to design simplified strategies for the control of grasping forces. Here, the number and the structures of the force synergies will be defined.’’Projecting synergies to the robotic hands with dissimilar kinematics ``Theoretical
tools to design a suitable mapping function of the control action (decomposed in its elemental action, synergies) from the paradigmatic hand domain onto the articulated hand co-domain. The definition of this mapping is the core of HANDS.DVI. Experiments ``The experiment consists of 3 robotic hands and an instrumented object with force sensors.’’ Slide14
Simplifying assumptions: objectsWith reference to the taxonomy [Curkosky], the different postures proposed in HANDS.DVI for the experiments will be- a power/prehensile/prismatic/heavy wrap grasp, also named cylindrical, characterized by a large diameter of the cylinder involved;- a
power/prehensile/circular grasp, characterized by a spherical configuration;- a precision/prismatic grasp, characterized by the opposition of the thumb and the other fingers.Ranging from heavy wrap power grasps to precision grasps, the above postures cut across the whole grasp choice space and, therefore, can be considered representative of the most common grasps a robotic hand would be asked to realize in hyper-flexible cells. Slide15
Simplifying assumptions: contactsThe force sensors are fixed to the object that will be referred to as the instrumented object. The instrumented object can change its shape but has given and fixed contact points. This is not a limitation since the focus of HANDS.DVI is on the control of contact force interaction and not on the approaching phase where the choice of contact points is importantFor a given shape of the object we will a–priori choose the optimal position of contact points on the object surface.Slide16
Three Tasks (UNISI,UNIPI,IIT)
HANDS.DVI
Shadow
Hand
Barrett
Hand
DLR II
Hand
Industrial
Gripper
Cooperative
Manipu-lators
task SYN
task DVI
task EXPSlide17Slide18Slide19Slide20
Mar ‘11
Jul ‘11Jul ‘11Jul ’11Jan’12May’11Mar’12’Slide21
Preliminary results UNISISlide22
The paradigmatic hand
Kinematic model of the hand @ UNISI (20 DoFs) Slide23
Matlab toolbox for grasp analysis with synergiesHand kinematicstructure (via DH parameters)
Hand reference configuration Synergy matrixdefinitionGrasped object: search the contact pointsGrasp Analysis Grasp optimization toolsSlide24Slide25Slide26Slide27Slide28Slide29
Task space mapping with ellipsoids
synergiessynergies ?MiddlewareReal handIn
the task frame.
Object-oriented.
- compute
the ellipsoids (force/manipulation) associated to the synergies in the paradigmatic space
- assign
those ellipsoid to the same object but with the real hand
- with
an inversion problem compute the
synergy mapping
This
is the synergy mapping for a given object and a given set of contacts. Slide30
Literature reviewEingengraps Mapping approaches (virtual finger)