Jean-Pierre Gazeau

A fast grasp synthesis method for online manipulation

This paper presents a new method for solving the grasp optimization problem by a multi-finger robotic hand; this method allows gripping an object using three articulated fingers, in order to manipulate it later. Because of the large number of operations and the high computation time, online grasp has not yet been reported. In this study, we propose a method that is able to provide an optimized initial grasp in a short time before online manipulation.

A real-time strategy for dexterous manipulation: Fingertips motion planning, force sensing and grasp stability

This paper presents a global strategy for object manipulation with the fingertips with an anthropomorphic dexterous hand: the LMS Hand of the ROBIOSS team from PPRIME Institute in Poitiers (France). Fine manipulation with the fingertips requires to compute on one hand, finger motions able to produce the desired object motion and on the other hand, it is necessary to ensure object stability with a real time scheme for the fingertip force computation. In the literature, lot of works propose to solve the stability problem, but most of these works are grasp oriented; it means that the use of the proposed methods are not easy to implement for online computation while the grasped object is moving inside the hand. Also simple real time schemes and experimental results with full-actuated mechanical hands using three fingers were not proposed or are extremely rare. Thus we wish to propose in a same strategy, a robust and simple way to solve the fingertip path planning and the fingertip force computation. First, finger path planning is based on a geometric approach, and on a contact modelling between the grasped object and the finger. And as force sensing is required for force control, a new original approach based on neural networks and on the use of tendon-driven joints is also used to evaluate the normal force acting on the finger distal phalanx. And an efficient algorithm that computes fingertip forces involved is presented in the case of three dimensional object grasps. Based on previous works, those forces are computed by using a robust optimization scheme. In order to validate this strategy, different grasps and different manipulation tasks are presented and detailed with a simulation software, SMAR, developed by the PPRIME Institute. And finally experimental results with the real hand illustrate the efficiency of the whole approach.

Lms robotic hand grasp and manipulation planning (an isomorphic exoskeleton approach)

In order to widen the potentialities of manipulation of the Laboratoire de Mecanique des solides (LMS) mechanical hand, we developed a new planning approach based on the use of a specific exoskeleton. This one has kinematics architecture and dimensions identical to the mechanical hand. This feature allows us to obtain manipulation trajectories for the mechanical hand, very easily and very quickly, by using the exoskeleton, without complex calibration. Manipulations trajectories are replayed offline with an autonomous control, and, consequently, the exoskeleton is not used with any feedback strategy for telemanipulation. This paper presents the characteristics of this exoskeleton and the graphic interface that we developed. This one uses a method to determine the objects evolution during the manipulation with the exoskeleton, without using exteroceptive sensors. This new approach was tested for standard trajectories by simulation on a Computer-aided design (CAD) robotics system and by using the mechanical hand. Thus, we validate the use concept of an isomorphic exoskeleton to mechanical hand for manipulation planning with the LMS mechanical hand.

A biomimetic reach and grasp approach for mechanical hands

Reach and grasp are the two key functions of human prehension. The Central Nervous System controls these two functions in a separate but interdependent way. The choice between different solutions to reach and grasp an object-provided by multiple and redundant degrees of freedom (dof)-depends both on the properties and on the use (affordance) of the object to be manipulated. This same control paradigm, i.e. subdivision of prehension into reach and grasp as well as the corresponding multimodal (sensory/motor) information fusion schemes, can also be applied to a mechanical hand carried by a robotic arm. The robotic arm will then be responsible for positioning the hand with respect to the object, and the hand will then grasp and manipulate the object. In this article, we present a biomimetic sensory-motor control scheme in the aim of providing an object-dependent and intelligent reach and grasp ability to such systems. The proposed model is based on a multi-network architecture which incorporates multiple Matching Units trained by a statistical learning algorithm (LWPR). Matching Units perform a multimodal signal integration by correlating sensory and motor information analogous to that observed in cerebral neuronal networks. The simulated network of multiple Matching Units provided estimations of object-dependent 5-finger grasp configurations with endpoint positional errors in the order of a few millimeters. For validation, these estimations were then applied to the control of movement kinematics on an experimental robot composed of a 6 dof robot arm carrying a 16 dof mechanical 4-finger hand. Precision of the kinematics control was such that successful reach, grasp and lift was obtained in all the tests.

New Printing Robot for High-Resolution Pictures on Three-Dimensional Wide Surfaces

A novel five-axes robot for industrial large printing applications is presented in this paper. The robot was developed in the robotics team from PRIME institute and an international patent was deposited for this invention in 2006. It concerns large-format 3-D printing on a fixed surface, like trailer tarpaulin for example. The robot is composed of an inkjet printing block and a device to dry the ink sprayed onto the surface. Kinematics of the mechanical device with 5 DOF was studied to position and orientate the printheads onto the surface to be printed. The structure of the robot is simple with high-speed capability and printing resolution. The working principle and mechanical structure are described, and the geometrical model and surface following control of the robot are also discussed. Finally, printing results in a practical situation illustrate the efficiency of the proposed 3-D printing robot, and an analysis of how the task is carried out is provided.

A novel 5-axis robot for printing high resolution pictures from media on 3D wide surfaces

A novel 5-axis robot for industrial large printing applications is presented in this paper. The robot was developed at the LMS1 from Poitiers University and an international patent [1] was deposited for this invention in 2006. It concerns large format three-dimensional printing on a fixed surface, like trailer tarpaulin for example. The robot is composed by an inkjet printing block and a device to dry the ink sprayed onto the surface. Kinematics of the mechanical device with 5 degrees of freedom was studied to position and orientate the printheads onto the surface to be printed. The structure of the robot is simple with high speed capability and printing resolution. The working principle and mechanical structure are described and the geometrical model and control of the robot are also discussed. Finally printing results illustrate the efficiency of the proposed 3D printing robot.

An industrial standard based control architecture for multi-robot real time coordination

This paper presents the challenges in the development of a new middleware for collaborative robotics and also for the new needs of interaction between robots and humans. The authors introduce first the main characteristics of a middleware; three types of middleware are proposed in the literature: Message Oriented Middleware, Middleware based on Remote Procedure Calls and also middleware based on the Object Request Broker. Thus a state of art of the most common middleware is given; ROS, RT-middleware and Orocos are detailed. Strong points and weak points are highlighted to justify the need to develop a new middleware. Based on this statement, the specifications of a new middleware are given with an important issue: develop a middleware that will meet complex research issues and also industrial issues for the future of robotics. In order to meet these issues, we propose the foundations of our approach. The middleware will be realtime, transferable, maintainable and multi-manufacturers. These requirements will also be able to guaranty the safety interaction of humans and machines in a dynamic and collaborative environment. Finally the efficiency of the proposed approach is demonstrated by using two different robots: a 6 dof industrial robot and a new 16 dof dextrous robot hand.

A peculiar flip-flop actuator for an in-pipe microrobot

The work presented here concerns the design and manufacturing possibility of a polymodular autonomous microrobot moving like an earthworm. The study consists of the development of a new locomotion actuator based on shape memory alloys. This actuator is formed by a flexible frame forced in post-buckling by its assembly on a rigid skeleton cage. This mechanical structure, forming a knot in the microrobot chain, uses its two post-buckling equilibrium positions to achieve first the support and second the local lengthening enabling the movement of the microrobot. Initially, we present the technical solution designed for the locomotion actuator and the mechanical characterization of its malleable structure. Then, we present the instrumentation by educated SMA of a malleable structure and the capability of microrobot locomotion task in a vertical tube.

Towards an Autonomous Airborne Robotic Agent

Commercialy available (UAVs) rely on the Global Positioning System (GPS) to define their flight plan, while assuming an obstacle-free environment. The work presented on this article aims to set the foundation towards an autonomous airborne agent, capable of locating itself by means of computer vision, modeling its environment, planning and executing a three dimensional trajectory. On the first stage of development we solved the localization problem using artificial markers and tested a PID controller to make the vehicle follows a given trajectory (a lemniscate); as results, we show flight data captured during real flights. This development would facilitate the integration of far more complex flight behaviors than GPS only guided flight plans.

Joint action with a virtual robotic vs. human agent

Abstract Prior research has revealed that when performing joint action tasks with a human co-actor, we automatically form representations not only of our own action, but also of the action of the co-actor we are interacting with, creating an action discrimination problem. Studies suggest these processes are affected by the human/non-human nature of the agent the task is shared with. In two experiments (Experiments 1 and 2), we measured the Joint Simon Effect (JSE) as an index of action discrimination, using a virtual version of the joint go/no-go task in which the task was shared with a virtual robotic vs. human hand. Furthermore, both experiments tested whether the JSE was affected by sensorimotor experience during which the participant manipulated the virtual robotic hand via an exoskeleton (vs. passive observation of movements of the virtual robotic hand). Experiment 2 replicated Experiment 1, except that prior to the joint action task, participants were informed about the robotic vs. human nature of the two virtual hands (no such information was given in Experiment 1). Both experiments demonstrated a significant JSE, which did not differ between robotic and human partner. Analysis of the results further indicates that the JSE obtained in the robotic condition was not modified after manipulating the virtual robotic hand. These results suggest that the human vs. non-human appearance of the partner is not a determinant of joint action performance in virtual settings.