This paper presents a new control scheme for dexterous manipulation of an object by a multifingered hand. The effects of the uncertainties on the contact orientation and location are investigated and taken into account in the control design, allowing to manipulate the object robustly. The control law has three main objectives: (i) ensuring the motion control of the object, (ii) satisfying the constraints of the manipulation system, and (iii) being robust to the uncertainties on the contact point. The proposed control is based on a state feedback architecture with robust pole placement by an LMI approach. The controller is designed offline and can be related to an object-level impedance controller. The constraints of the manipulation system, e.g. the friction constraints, are taken into account with an additional control action, based on an online LMI evaluation. Simulation results are presented and demonstrate that the proposed control law ensures the three main objectives.

This paper presents a new control scheme for dexterous manipulation of an object by a multifingered hand. The aim of this control is to ensure the tracking by the object of specific trajectories depending on the task. More specifically, we consider a decoupling control according to the motion directions in the task space. The control scheme is based on a new eigenstructure assignment method, where the placement of the closed-loop eigenvalues ensures the stability of the system hand/object, and the strict placement of the object-level eigenvectors ensures the system decoupling. A parallel is made between task specifications and synergies. Current synergy controllers are often bio-inspired and based on the analysis of synergies in the human hand. The proposed algorithm allows the specification of precise object level performance according to the task, and to find the related synergies. Moreover, robustness to uncertainties on the contact point is an additional objective of the control law, and the effect of these uncertainties on the decoupling is investigated. Simulation results are presented and illustrate the decoupling effect of the control law on the system hand/object in the 2D-cartesian space.

This paper presents a tactile sensing system capable of measuring three force components, three torque components and the position of the centroid of the forces applied to a surface linked to an array of force-torque sensors. The paper deals with the design, the calibration, and the testing of a specific configuration of this system, where the surface is connected to an array of piezoresistive MEMs silicon 3-axis force sensors. In this configuration, only the contact position and the force components are estimated. The tests have proven that this sensor satisfies most of the characteristics needed to achieve robotic dexterous manipulation.

This paper presents a stable control method for a hybrid haptic device comprising a brake and a motor. A review of stability condition via describing function analysis is first presented. The results show that while brakes are intrinsically stable, an active device is limited in terms of stiffness. The stability is however improved if the brake simulates a physical damping. Subsequently, the stability condition is obtained via passivity condition analysis. The results demonstrate that the stiffness is improved by engaging both actuators to create resistive forces and the passivity is respected assuming a passive virtual environment. An energy and a stiffness-bounding algorithms have been developed in order to assure the stability of the coupled system in this case. It has been tested and validated using a 1-DOF hybrid haptic device by the simulation of an unstable and an active virtual environments respectively . Experimental results show that the displayable stiffness is improved under stability conditions using the control method. Furthermore, it allows the hybrid system to simulate nonlinear and unstable virtual environments and the controller remains independent of the virtual environment model.

This paper presents a method for humanoid push recovery in the general context of multiple non-coplanar contacts. The method consists of a controller that minimizes the kinetic energy of a perturbed whole body humanoid system, while controlling the support change to achieve the stabilization (or push recovery) of the system. The controller uses a simple model based approach to determine the necessity of support change and in this case to approximate a new contact position that allows to stabilize the system. The controller is tested on a simulated humanoid robot and it succeeds in stabilizing the robot in coplanar and non-coplanar environments.

A new concept of hybrid actuator for haptic devices is proposed. This system combines a controllable magnetorheological brake with a conventional DC motor. Both actuators are linked through an overrunning clutch. Thus, the motor is connected to the handle while the brake can exert a resistive force only in a defined direction. This configuration enables the brake and the motor to be engaged at the same time because the torque imposed by the motor is not canceled by the brake. The concept and its control laws have been investigated using a 1-DOF haptic device. The experimental results show that is possible to combine a powerful brake with a small DC motor. This approach reduces the power consumption, expand the range of forces, achieve global stability in the system providing thereby safety to the user. Besides, the proposed independent control laws enable the actuator to be adaptable in many different haptic applications.

This paper presents a new control framework for virtual humans (VHs) in a physics-based virtual environment. This framework combines multiobjective control with motion capture techniques. Each motion-tracking task is associated with a task wrench. Bounds are imposed on lower priority task wrenches to ensure the controller performance of higher priority tasks. An optimization problem is solved to compute optimal task wrenches that are based on wrench bounds. Finally, joint torques are computed using the optimal task wrenches. The novelty of our wrench-bound method is that it can handle inequality constraints on a higher priority task and maintain passivity as well. This control framework allows an operator to interact with the VH in real time, without the necessity of compromising the VH's balance. It also allows the VH to generate appropriate motions to handle interactions with the virtual environment, rather than to simply emulate captured motions. The effectiveness of our approach is demonstrated by a VH performing reaching and manipulation tasks.

This paper proposes a new framework of online hybrid control for virtual characters, which combines multi-objective control and motion capture techniques. At each time step, the motions of the operator are captured and sent to the character. These captured motions help the character understand what task the operator wants it to perform. Then, the character decides by itself how to execute proper actions while maintaining its balance, in a virtual environment which is different from the real world. Given a manipulation task, the desired virtual task wrench is computed thanks to a force control approach. The control system takes these task wrenches into consideration and solves a constrained quadratic problem for joint torques, which are then used to drive the virtual character. The whole control problem is solved online so that the virtual character can interact in real-time with the virtual environment as well as the operator. Examples using this control framework are presented as results from simulation.

This paper presents a new computational approach for humanoid push recovery in a generalized noncoplanar multicontact context. Our approach is based on a simplified model and consists of two main steps. The first one predicts whether the perturbed system can be stopped in a final static state while maintaining fixed contacts with the environment. This prediction can be seen as a dynamic stability indicator. The second one consists of a strategy that stabilizes the system, when stability cannot be reached, through a contact change chosen as the best one among a set of a priori possible contact changes.

In the reinforcement learning literature, transfer is the capability to reuse on a new problem what has been learnt from previous experiences on similar problems. Adapting transfer properties for robotics is a useful challenge because it can reduce the time spent in the first exploration phase on a new problem. In this paper we present a transfer framework adapted to the case of a climbing virtual human (VH). We show that our VH learns faster to climb a wall after having learnt on a different previous wall.

We address the problem of choosing adequate contact forces to ensure the stability of a multi-fingered grasp in face of external disturbances of unknown intensity. The contact forces we look for are tightening, pre-strain forces rather than active, direction-related blocking forces. We compute such tightening forces, together with blocking forces and a lower-bound approximation of an existing grasp quality measure, in only one linear programming problem. The tightening forces ensure robustness to the largest-minimum resisted disturbance wrench, but a variety of optimal contact forces may be further computed from the desired robustness by solving a quadratic programming problem.

While realizing a task, human-beings are able to use grasping inside their environment in order to keep the most stable balance. Although such a behavior is quite natural for humans, it is very difficult to find the best formulation to adapt human motion to humanoid robots. This paper proposes a conceptually simple framework of human posture control based on optimization which takes into account grasp and friction and achieves robustness against external disturbances. A new stability criteria is also introduced. Contrary to most other approaches, our method deals not only with unilateral contacts with friction but also with bilateral grasps. This allows for arbitrarily pulling, pushing or twisting on a handhold. Additionally, and in contrast to classical methods based on ZMP, our method also accounts for contacts not being all in the same plane.

This paper presents a new method for a six degrees of freedom haptic feedback in molecular docking simulations in virtual reality. The proposed method allows real-time haptic interaction even in the case of classical molecular simulation which implies notoriously long computation time. These simulations are classically used by the pharmaceutical industry (Sanofi-Aventis) and are based on the energetic description of atoms to estimate the interaction between a ligand and a protein. The haptic control scheme uses wave variables for a stable and robust teleoperation, and a transcription of the calculated energy into forces and torques for the manipulation of a flexible ligand around the binding site of a flexible molecule. This method can then be used with any energetic force field using a minimization process, thus avoiding the fastidious optimization of molecular simulation programs.

This paper proposes a novel planning algorithm for image based visual servoing (IBVS). IBVS is conceptually simple but prone to fail in case of large displacements. Hence, the objective is to provide paths for reference points in the image plane, such that the camera is steered from initial position to desired position. The novel scheme guarantees that the camera is always oriented such that the object of interest is in the field of view and that any reference point set corresponds indeed to a feasible camera pose. No camera calibration is necessary. As a novelty, this work is planning a camera motion, hence yielding compact paths in robot work space. The proposed planner is compared to others by experiments.

This paper presents a new method allowing haptic feedback in molecular docking simulations using a minimization process. These simulations, classically used by the pharmaceutical industry, for example Sanofl-Aventis, are based on the energy description of atoms to estimate the interactions between a ligand and a protein. The main drawback is that forces and torques cannot be calculated by the means of a simple derivation. The proposed method is to locally build an energy model, the shape of which is correctly predetermined, depending on parameters to be estimated, themselves functions of the energy of the interatomic interactions and of the displacement of the haptic device. The interaction's wrench can be obtained using an analytic derivation of the energy model. The molecular simulator does not need to be optimized or modified, only the calculated interaction energy is used to build a model which will interact with the haptic device. This new method can then be used with any force field using a minimization process, ensuring stable manipulation, and a low- force dynamic, therefore allowing comprehensive and stable force feedback.

In this article, the problem of force feedback control of kinematically constrained manipulators (KCMs) is considered. For these robots, we show that the force component selection approach is not appropriate in general to solve the force control problem. Moreover, by formulating the problem in the joint space, we show how to properly design a stable force controller for KCMs subject to arbitrary external forces applied to their end-effector. Experimental results with a kinematically constrained laparoscopic comanipulator illustrate these propositions

This paper presents a control approach for human grasp simulation in a real-time context. We consider a 12-dof hand grasping quasi-rigid objects, either for fine manipulation or perturbation rejection. The objective is to translate and rotate the object with respect to non-sliding conditions. In order to improve the visual realism and the stability of the simulation, we use a locally deformable model on fingertips with friction. The resolution of contact forces is used for controlling the system with a set of 23 muscles. This paper presents also a new technique for solving the grasping force optimization problem, allowing real time simulation. This work is part of a virtual human project and combines robotic control experiments and theoretical laws of deformations in a global simulation

In the present paper, we introduce a new control architecture aimed at driving virtual humans in interaction with virtual environments, by motion capture. It brings decoupling of functionalities, and also of stability thanks to passivity. We show projections can break passivity, and thus must be used carefully. Our control scheme enables task space and internal control, contact, and joint limits management. Thanks to passivity, it can be easily extended. Besides, we introduce a new tool as for manikin's control, which makes it able to build passive projections, so as to guide the virtual manikin when sharp movements are needed.

Trajectory planning for eye-in-hand visual servoing is usually performed in the Euclidean work space of the robot or in a two dimensional image space. However, planning in Euclidean space may lead to very inappropriate trajectories in image space and vice versa. These difficulties are due to the perspective transformation of the camera, loss of one dimension due to projection onto the image plane and the fact that only a rough approximation of camera parameters is practically available. Hence, this paper proposes a planning scheme for image trajectories such that straight line behaviour is ensured both in image space and world space, ie. a single but arbitrarily chosen point in the image plane performs straight line behaviour as well as the camera optical center in work space. This way, trajectories become very compact and most of the above mentioned problems are avoided in a natural way. The algorithm requires as a priori information nothing more than matched image points (in pixels) from a current and desired image and a depth set for at least one position.

This paper presents a remote handling force feedback coupling for micromanipulation systems. In the literature, the most generally used coupling mode is 'force position'. This kind of control scheme is not portable and instability is an often occurring problem. The coupling scheme proposed in this paper is based on the passivity considerations on the teleoperated systems. It is independent of the used haptic interface and the manipulator and unconditionally stable regarding scaling ratios. It is experimented using the LRP's (Laboratoire de Robotique de Paris) micromanipulator, which is based on AFM architecture and uses the adhesion forces for pickup and release tasks. A comparison between the force position coupling and proposed coupling is presented. Experimental results show the good performances in terms of stability.

This work presents a novel visual servoing approach, aimed at controlling the so-called extended-2D (E2D) coordinates of the points constituting a tracked target. This approach does not require any pose reconstruction. Rather, the only information required to build the E2D coordinates are the estimated depth distribution of the target points, and the estimated camera model. Several implementations of the controller are considered, which are inspired from conventional image based visual servoing from points. In spite of their simplicity, the proposed control laws exhibit remarkable stability robustness properties. A key issue is that only three configurations of undesired equilibrium exist, and they are all proven to be unstable even in the uncalibrated case. In other words, contrarily to existing 2D methods, there are no local minima. The paper details the control design and analysis and provides simulation results, emphasizing the remarkable robustness with respect to camera calibration errors.

Using an industrial manipulator as a slave arm in a force-feedback teleoperation system requires to us deal with its poor backdrivability. Improving transparency of such a system, using a wrist force/torque sensor, is known as an effective and robust method. Another solution could be to use a base force/torque sensor. The paper focuses on the feasibility of such an approach in a force-feedback teleoperation context. It is then compared to a wrist force/torque sensor approach.

Tuning a telemanipulation system is still a real challenge. The task model is often unknown, the system must remain stable for a wide range of tasks, configurations, for different modes which share in a different way all the system degrees of freedom. Thinking of numerous controllers which come up with all these different situations is quite unrealistic. In fact, a compromise between the number of control parameters and the system performances has to be found. Here, we propose a method for the design of a decoupling controller allowing different tunings along teleoperated DOF and locally controlled ones.

This paper deals with state feedback control of nonholonomic systems whose configuration space presents some singular points. The whole study is driven on the example of mobile robots equipped with several steering wheels. Linearizing dynamic feedback and time-varying feedback are successively considered to handle the tracking of a moving reference trajectory and the stabilization of the robots to a rest configuration, respectively. Both laws are designed in such a way that the systems singular configurations cannot definitely be met. Finally, a commutation procedure between the two laws is presented, in order to handle the very natural problem of tracking a reference trajectory ended by a rest configuration.

This paper presents a feedback nonlinear control law for a train-like vehicle (TLV) used in nuclear power-station maintenance. The front cart is either manual or automated guided. The rear carts are feedback controlled. The control objective is to ensure that the rear carts track the path produced (online) by the front cart. This controller was experimentally tested on the TLV-prototype.>