This paper proposes a proportional plus damping injection (P + d) controller for bilateral teleoperators in the operational space. Unit quaternions are used to describe the end-effectors' orientation since they exhibit the well known property of being a singularity-free representation. The proposed controller does not need the measurement of the velocities, instead a passivity-based filter is used. Under the reasonable assumptions that the human operator and the environment define passive maps from force to velocity, it is proved that velocities and pose (position and orientation) errors between the local and the remote manipulators are bounded. Moreover, in the case that the human and the environment forces are zero, the velocities and pose errors converge asymptotically to zero. Finally, experimental validation using two robots of 6-Degrees-of-Freedom (DoF) shows the effectiveness of the proposed control scheme.

It is widely known that the problem of controlling a rigid bilateral teleoperator with time-delays has been effectively addressed since the late 80's. However, the control of flexible joint manipulators in a bilateral teleoperation scenario, with dynamic gravity compensation, remains an open problem. This work aims at filling this gap by presenting a new controller for bilateral teleoperators composed of a rigid local manipulator and a flexible-joint remote manipulator with dynamic gravity compensation and asymmetric variable time-delays in the communication channel. In order to dynamically compensate the gravity term, in the flexible joint manipulator, a change of coordinates which accounts for the joint and link gravity position drift is used. The rest of the controller is a simple PD scheme. Assuming that the human operator and the environment define passive maps from velocity to force, it is proved that velocities and local and remote position errors are bounded. Additionally, if the human operator and remote environment forces are zero then velocities asymptotically converge to zero and position tracking is established. Some simulations are presented in order to show the performance of the proposed controllers.

The present paper proposes two controllers for solving a consensus problem to a given desired position of networks composed of a class of under actuated mechanical systems: flexible joints robots. One of the controllers makes use of joint (motor) velocity signals while the other only uses joint positions. The only assumption on the directed and weighted interconnection graph is that it is connected. Further, the interconnection may induce variable time-delays. The paper presents some experiments, using three 3-Degrees of Freedom manipulators, which show the performance of the proposed approaches.

This paper presents a proportional plus damping controller that can asymptotically drive a network composed of N nonidentical Euler-Lagrange (EL) systems toward a consensus point. The agents can be fully actuated or can belong to a class of underactuated EL-systems. The network is modeled as a weighted and undirected static interconnection graph that can exhibit asymmetric variable time delays. Simulations, using a network with ten EL-systems, are reported to support the theoretical contributions of this study.

This paper presents an adaptive controller for the bilateral teleoperation of a system composed by a single local manipulator and multiple cooperative remote manipulators handling a common object. First, the nonlinear operational space dynamical behavior of the complete teleoperation system is derived. Then, under the assumptions that the remote manipulators are rigidly grasping a non-deformable object and that the communications may induce constant time-delays, it is proved that velocities and position-orientation error between the local manipulator end-effector and the object asymptotically converge to zero. Simulations results are included to show the effectiveness of the proposed approach.

The problem of controlling a rigid bilateral teleoperator with time-delays has been effectively addressed since the late 80's. However, the control of flexible joint manipulators in a bilateral teleoperation scenario is still an open problem. In the present paper we report two versions of a proportional plus damping injection controller that are capable of globally stabilizing a nonlinear bilateral teleoperator with joint flexibility and variable time-delays. The first version controls a teleoperator composed by a rigid local manipulator and a flexible joint remote manipulator and the second version deals with local and remote manipulators with joint flexibility. For both schemes, it is proved that the joint and motor velocities and the local and remote position error are bounded. Moreover, if the human operator and remote environment forces are zero then velocities asymptotically converge to zero and position tracking is established. Simulations are presented to show the performance of the proposed controllers.

This paper presents two versions of adaptive controllers for nonlinear bilateral teleoperators, each providing asymptotic convergence of velocity and position errors to zero, independent of constant time-delays. Moreover, the proposed schemes do not rely on the use of the scattering transformation. The paper also proves that the teleoperator is Input-to-State Stable from human operator and environment inputs to some synchronization signals. Simulations show the effectiveness of the proposed controllers.

Two controllers capable of achieving asymptotic convergence of position and velocity errors, of the ith-manipulator within a multiple robot network, are proposed. The controllers employ adaptive techniques to find an estimate of the physical parameters of the nonlinear dynamics of the robot network. Moreover, the controllers can deal with different connectivity topologies (ring and star) and and can handle time-delays in the communications. Simulations, using a ten robot manipulators network with different connectivity topologies, that confirm the theoretical results are presented.

This work presents a multimodal teleoperation framework that makes use of novel tools and techniques, such as: nonlinear teleoperators control, for ensuring position tracking in the presence of variable time-delays; relational positioning, for increasing operator performance on precise movement execution by visually and haptically displaying geometric constraints; and augmented reality, for visually combining real and virtual information in a compelling way. Experimental evidence is presented that validates the aptitude of the different components of the proposed framework.

This paper aims to take a first step towards the unification of the stability analysis for teleoperators with time-delays. It proposes a general Lyapunov-like function that, upon slight modification, allows to analyze the stability of different control schemes, ranging from constant to variable time delays, with or without the scattering transformation and with or without position tracking. It also presents design examples of the corresponding Lyapunov-like function for some schemes based on PD controllers and on the scattering transformation for variable time-delays.

This paper extends the previous results on position tracking for bilateral teleoperators with constant time-delays, reported in Nuno et al. IEEE Trans. Robot., vol. 24, no. 3, pp. 753-758, June 2008, to the case of variable time-delays in the teleoperator's communications. The key part is the extension of a previous Lemma that is used to prove that P+d or PD+d controllers can stabilize the teleoperator under variable timedelays, and moreover, they provide position tracking. The paper outlines the conditions under which velocities and position errors, of the nonlinear teleoperator, are bounded, and using Barbalat's Lemma, it is proved asymptotic converge to zero if the local manipulator stands still and the remote manipulator does not interact with the environment. Simulations and real experiments validate the proposed schemes. The experiments have been performed using the Internet as communication channel between Urbana-Champaign, USA and Barcelona, Spain.

One of the key factors that affect the success and efficiency of sampling-based path planners is the obtention of samples in the more relevant regions of the workspace. This is known as importance sampling, and different approaches have already been proposed in this direction. This paper proposes a novel method to bias sampling by means of geometric constraints that reduces the sampling space to sets of lower dimensional submanifolds. These constraints may be imposed by the kinematic structure of the actuation system, by the task specification, or provided by a human user as an intuitive way to include problem knowledge to the planner. The method has been implemented and tested on a probabilistic roadmap planner giving promising results. A variant using a deterministic sampling source is also reported.

This paper presents a framework that enables an operator to haptically and visually interact with a simulated dynamic environment subject to virtual holonomic constraints. The framework combines a geometric constraint solver with a constrained dynamics simulation engine that controls an admittance-type haptic display. This system takes on relevant issues in the context of assisted teleoperated tasks, from providing an intuitive interface for creating and combining virtual constraints, to haptically displaying rigid motion constraints in simulated environments subject to desired inertial dynamics. Two experiments carried out using the Cobotic Hand Controller haptic display are presented.

In a recent scheme, with delayed derivative action [Lee and Spong,IEEE Trans. Robot., vol. 22, no. 2, pp. 269--281, Apr. 2006], it is claimed that a simple proportional derivative (PD) scheme yields a stable operation. Unfortunately, the stability proof hinges upon unverifiable assumptions on the human and contact environment operators, namely, that they define${\cal L}_\infty$--stable mapsfrom velocity to force. In this short paper, we prove that it is indeed possible to achieve stable behavior with simple PD-like schemes---even without the delayed derivative action---under the classical assumption of passivity of the terminal operators.

This paper presents a relational positioning methodology that allows to restrict totally or partially the movements of an object by specifying its allowed positions in terms of a set of intuitive geometric constraints. In order to derive these positions, ageometric constraint solvermust be used. To this end, positioning mobile with respect to fixed (PMF), a geometric constraint solver for the relational positioning of rigid objects in free space is introduced. The solver exploits the fact that, in a set of geometric constraints, the rotational component can often be separated from the translational one and solved independently. PMF may be used as an interface for specifying offline-programmed robot tasks, as well as for assisting the execution of teleoperated tasks requiring constrained movements. Examples describing both the solver's operation and typical applications are discussed.

This paper addresses the problem of stable bilateral teleoperation, through a time-delayed communication channel, for a n-DOF system without position drift. The classical wave variables-based scheme encodes velocity and force whilst the proposed scheme encodes position and integral of force. The resulting passive communication scheme is used in an extended teleoperation framework, in which the human operator can define geometrical motion restrictions in order to increase his awareness and his feeling of immersion, hence improving his ability to perform complex tasks. The framework also provides the operator with video feedback and 3D rendering of the remote scene.

The performance of tasks with robots in environments with low clearances (e.g. robotized assembly) is usually difficult, due mainly to geometric uncertainty and tolerances. Following a pragmatical approach to planar constrained-motion planning, this paper proposes a method for checking the feasibility of paths generated by gross-motion planning algorithms, taking into account the uncertainties affecting the task and the use of a compliant control mode. The method enables the extension of gross-motion planning techniques to constrained-motion planning problems, ensuring the feasibility of the task despite the uncertainties.

Describes an efficient technique for computing a hierarchical representation of the objects contained in a complex 3D scene. First, an adjacency graph keeping the costs of grouping the different pairs of objects in the scene is built. Then the minimum spanning tree (MST) of that graph is determined. A binary clustering tree (BCT) is obtained from the MST. Finally, a merging stage joins the adjacent nodes in the BCT which have similar costs. The final result is an n-ary tree which defines an intuitive clustering of the objects of the scene at different levels of abstraction. Experimental results with synthetic 3D scenes are presented.

This paper presents a method for the planning and execution of compliant motions within the scope of a two-phase fine-motion planner for the performance of planar assembly tasks with robots. Algorithms are provided to find a nominal solution path in both free and contact configuration space which is feasible in spite of the uncertainties affecting the task. Compliant-motion commands based on the generalized damping control mode are synthesized to follow this path, allowing to maintain a constant bounded force.

Presents a technique for determining a small set of views that allow the observation and acquisition of the surfaces of the objects present in a target scene through a range sensor that moves over a sphere containing that scene. No a priori knowledge about the shape of those objects is assumed. Instead of applying costly visibility analysis techniques from the beginning as in most previous approaches, a two-stage algorithm is proposed. The first stage is responsible for getting the majority of object surfaces through a voting scheme based on occlusion edges. Then, a second stage applies visibility analysis to fill holes left by the first stage due to self-occlusions.

The paper presents an efficient algorithm for generating adaptive triangular meshes from dense range images. The proposed technique consists of two stages. First, a quadrilateral mesh is generated from the given range image. The points of this mesh adapt to the surface shapes represented in the range image by grouping in areas of high curvature and dispersing in low-variation regions. The second stage splits each quadrilateral cell obtained before into two triangles. Between the two possible flips, it is chosen the one whose diagonal's direction is closest to the orientation of the discontinuities present in that cell. Both stages avoid costly iterative optimization techniques. Results with real range images are presented. They show low CPU times and accurate triangular approximations of the given images.

This paper proposes a fast technique for generating adaptive quadrilateral meshes from range images with no optimization. The obtained meshes adapt to the features of the input images by concentrating points in areas of high curvature and by dispersing them in low variation regions. This leads to more accurate approximations of the given range images than when uniform sampling with the same number of points is applied. Experimental results with real range images representing both free-form and polyhedral and cylindrical objects are presented.

This paper presents the graphical embedding of the rotational degree of freedom into the translational configuration space for planar assembly tasks. The resulting representation helps the visualization and understanding of motions in a simple and easy graphical way. The aim is the developing of motion planning algorithms in a two-dimensional parametrized space for planar assembly tasks (3 DOF) and in a three-dimensional parametrized space for assembly tasks in space (6 DOF). The method has been successfully applied to the problem of contact identification in the presence of uncertainty for planar assembly tasks. The extension to six degrees of freedom is under development.

Force-compliant control is an important aspect for performing assembly tasks with robots, since the geometric constraints of the task are usually used as guides. The paper presents the specification of compliant motions for planar assembly tasks (two degrees of freedom of translation and one of rotation), taking into account the effect of friction.

An efficient algorithm for extracting planar and curved surface patches that express distinctive parts of the objects contained in a given range image is presented. The proposed technique does not directly segment the range image but a triangular approximation of it obtained through a fast adaptive randomized sampling algorithm. This intermediate representation allows us to avoid the processing of all the individual points of the range image in the segmentation phase.

This paper describes the use of a previously developed surface model for representing 3D geometric information that is subject to uncertainty. The proposed model is based on a geometric data fusion technique that allows the efficient approximation of arbitrary triangular meshes in space with smooth surfaces. This paper shows how the shape modifiers defined in the model can be used to represent both global and local uncertainty associated with the input data. The possibility of handling scattered 3D points, taking into account their corresponding uncertainties, makes this technique a suitable tool for modeling free-form surfaces acquired through sensing, as well as for integrating 3D data obtained from multiple sensors with different associated confidences.

The authors propose a robotic assembly system that is based on the least-commitment principle, in which the successive stages proceeding from planning to execution become progressively more specific. The system is partitioned into an offline automatic programming system and an online execution manager. The framework and objectives are presented, followed by an overview of the global system. The submodules of a system that has actually executed a simple pick/place task are described. Some conclusions and perspectives are outlined.>