A Stability Analysis for the Acceleration-based Robust Position Control of Robot Manipulators via Disturbance Observer

This paper proposes a new nonlinear stability analysis for the acceleration-based robust position control of robot manipulators by using Disturbance Observer (DOb). It is shown that if the nominal inertia matrix is properly tuned in the design of DOb, then the position error asymptotically goes to zero in regulation control and is uniformly ultimately bounded in trajectory tracking control. As the bandwidth of DOb and the nominal inertia matrix are increased, the bound of error shrinks, i.e., the robust stability and performance of the position control system are improved. However, neither the bandwidth of DOb nor the nominal inertia matrix can be freely increased due to practical design constraints, e.g., the robust position controller becomes more noise sensitive when they are increased. The proposed stability analysis provides insights regarding the dynamic behavior of DOb-based robust motion control systems. It is theoretically and experimentally proved that non-diagonal elements of the nominal inertia matrix are useful to improve the stability and adjust the trade-off between the robustness and noise sensitivity. The validity of the proposal is verified by simulation and experimental results.Comment: 9 pages, 9 figures, Journa

Issues, concerns, and initial implementation results for space based telerobotic control

Telerobotic control for space based assembly and servicing tasks presents many problems in system design. Traditional force reflection teleoperation schemes are not well suited to this application, and the approaches to compliance control via computer algorithms have yet to see significant testing and comparison. These observations are discussed in detail, as well as the concerns they raise for imminent design and testing of space robotic systems. As an example of the detailed technical work yet to be done before such systems can be specified, a particular approach to providing manipulator compliance is examined experimentally and through modeling and analysis. This yields some initial insight into the limitations and design trade-offs for this class of manipulator control schemes. Implications of this investigation for space based telerobots are discussed in detail

A spatial impedance controller for robotic manipulation

Mechanical impedance is the dynamic generalization of stiffness, and determines interactive behavior by definition. Although the argument for explicitly controlling impedance is strong, impedance control has had only a modest impact on robotic manipulator control practice. This is due in part to the fact that it is difficult to select suitable impedances given tasks. A spatial impedance controller is presented that simplifies impedance selection. Impedance is characterized using ¿spatially affine¿ families of compliance and damping, which are characterized by nonspatial and spatial parameters. Nonspatial parameters are selected independently of configuration of the object with which the robot must interact. Spatial parameters depend on object configurations, but transform in an intuitive, well-defined way. Control laws corresponding to these compliance and damping families are derived assuming a commonly used robot model. While the compliance control law was implemented in simulation and on a real robot, this paper emphasizes the underlying theor

On-line Joint Limit Avoidance for Torque Controlled Robots by Joint Space Parametrization

This paper proposes control laws ensuring the stabilization of a time-varying desired joint trajectory, as well as joint limit avoidance, in the case of fully-actuated manipulators. The key idea is to perform a parametrization of the feasible joint space in terms of exogenous states. It follows that the control of these states allows for joint limit avoidance. One of the main outcomes of this paper is that position terms in control laws are replaced by parametrized terms, where joint limits must be avoided. Stability and convergence of time-varying reference trajectories obtained with the proposed method are demonstrated to be in the sense of Lyapunov. The introduced control laws are verified by carrying out experiments on two degrees-of-freedom of the humanoid robot iCub.Comment: 8 pages, 4 figures. Submitted to the 2016 IEEE-RAS International Conference on Humanoid Robot

Nonlinear robust controller design for multi-robot systems with unknown payloads

This work is concerned with the control problem of a multi-robot system handling a payload with unknown mass properties. Force constraints at the grasp points are considered. Robust control schemes are proposed that cope with the model uncertainty and achieve asymptotic path tracking. To deal with the force constraints, a strategy for optimally sharing the task is suggested. This strategy basically consists of two steps. The first detects the robots that need help and the second arranges that help. It is shown that the overall system is not only robust to uncertain payload parameters, but also satisfies the force constraints

Human machine interaction via the transfer of power and information signals

Robot manipulators are designed to perform tasks which would otherwise be executed by a human operator. No manipulator can even approach the speed and accuracy with which humans execute these tasks. But manipulators have the capability to exceed human ability in one particular area: strength. Through any reasonable observation and experience, the human's ability to perform a variety of physical tasks is limited not by his intelligence, but by his physical strength. If, in the appropriate environment, we can more closely integrate the mechanical power of a machine with intellectually driven human hand under the supervisory control of the human's intellect, we will then have a system which is superior to a loosely-integrated combination of a human and his fully automated robot as in the present day robotic systems. We must therefore develop a fundamental approach to the problem of this extending human mechanical power in certain environments. Extenders will be a class of robots worn by humans to increase human mechanical ability, while the wearer's intellect remains the central intelligent control system for manipulating the extender. The human body, in physical contact with the extender, exchanges information signals and power with the extender. Commands are transferred to the extender via the contact forces between the wearer and the extender as opposed to use of joystick (master arm), push-button or key-board to execute such commands that were used in previous man amplifiers. Instead, the operator becomes an integral part of the extender while executing the task. In this unique configuration the mechanical power transfer between the human and extender occurs in addition to information signal transfer. When the wearer uses the extender to touch and manipulate an object, the extender transfers to the wearer's hand, in feedback fashion, a scaled-down value of the actual external load which the extender is manipulating. This natural feedback force on the wearer's hand allows him to feel the scaled-down value of the external forces in the manipulations. Extenders can be utilized to maneuver very heavy loads in factories, shipyards, airports, and construction sites. In some instances, for example, extenders can replace forklifts. The experimental results for a prototype extender are discussed

Integral Resonant Control for vibration damping and precise tip-positioning of a single-link flexible manipulator

Peer reviewedPostprin

Robust Cooperative Manipulation without Force/Torque Measurements: Control Design and Experiments

This paper presents two novel control methodologies for the cooperative manipulation of an object by N robotic agents. Firstly, we design an adaptive control protocol which employs quaternion feedback for the object orientation to avoid potential representation singularities. Secondly, we propose a control protocol that guarantees predefined transient and steady-state performance for the object trajectory. Both methodologies are decentralized, since the agents calculate their own signals without communicating with each other, as well as robust to external disturbances and model uncertainties. Moreover, we consider that the grasping points are rigid, and avoid the need for force/torque measurements. Load distribution is also included via a grasp matrix pseudo-inverse to account for potential differences in the agents' power capabilities. Finally, simulation and experimental results with two robotic arms verify the theoretical findings