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

Position and force control with mass estimation for cooperative systems

[ES] La manipulación cooperativa de un objeto por dos o más brazos robóticos requiere controlar tanto el movimiento del objeto como las fuerzas ejercidas por los manipuladores. En términos de cinemática y estática, el enfoque elegido se basa en la denominada formulación simétrica. Se diseña un algoritmo de control que utiliza una modificación del método híbrido de torque computarizado basado en el Principio de Ortogonalización. Además, la masa del objeto se estima calculando la fuerza aplicada por cada efector final para sostener el objeto. El método propuesto es una extensión natural del esquema de control adaptativo previamente reportado para manipuladores geométricamente restringidos. La prueba de estabilidad se desarrolla utilizando la teoría de Lyapunov. Se presentan resultados experimentales.[EN] The cooperative manipulation of an object by two or more robotic arms requires controlling both the object’s movement and the forces exerted by the manipulators. In terms of kinematics and static, the chosen approach is based on the so–called symmetric formulation. A control algorithm using a modified hybrid computed–torque method based on the Principle of Orthogonalization is designed. In addition, the mass of the object is estimated by calculating the force applied by each end–effector to hold the object. The proposed method is a natural extension of an adaptive control scheme previously reported for geometrically restricted manipulators. The stability test is developed using Lyapunov’s theory. Experimental results are presented.Los autores agradecen a PRODEP (PROMEP) con el folio BUAP–811 y al proyecto PAPIIT IN117820.Sánchez-Sánchez, P.; Arteaga-Pérez, MA. (2020). Control de posición y fuerza con estimación de masa para sistemas cooperativos. Revista Iberoamericana de Automática e Informática industrial. 17(4):368-379. https://doi.org/10.4995/riai.2020.12432OJS368379174Arimoto, S. and Liu, Y. H. and Naniwa, T., 1993. 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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

Fuzzy logic control of telerobot manipulators

Telerobot systems for advanced applications will require manipulators with redundant 'degrees of freedom' (DOF) that are capable of adapting manipulator configurations to avoid obstacles while achieving the user specified goal. Conventional methods for control of manipulators (based on solution of the inverse kinematics) cannot be easily extended to these situations. Fuzzy logic control offers a possible solution to these needs. A current research program at SRI developed a fuzzy logic controller for a redundant, 4 DOF, planar manipulator. The manipulator end point trajectory can be specified by either a computer program (robot mode) or by manual input (teleoperator). The approach used expresses end-point error and the location of manipulator joints as fuzzy variables. Joint motions are determined by a fuzzy rule set without requiring solution of the inverse kinematics. Additional rules for sensor data, obstacle avoidance and preferred manipulator configuration, e.g., 'righty' or 'lefty', are easily accommodated. The procedure used to generate the fuzzy rules can be extended to higher DOF systems

Multiple cooperating manipulators: The case of kinematically redundant arms

Existing work concerning two or more manipulators simultaneously grasping and transferring a common load is continued and extended. Specifically considered is the case of one or more arms being kinematically redundant. Some existing results in the modeling and control of single redundant arms and multiple manipulators are reviewed. The cooperating situation is modeled in terms of a set of coordinates representing object motion and internal object squeezing. Nominal trajectories in these coordinates are produced via actuator load distribution algorithms introduced previously. A controller is developed to track these desired object trajectories while making use of the kinematic redundancy to additionally aid the cooperation and coordination of the system. It is shown how the existence of kinematic redundancy within the system may be used to enhance the degree of cooperation achievable

Predictive Adaptive Control of Multiple Robots in Cooperative Motion

In this paper we address the problem of controlling multiple robots manipulating a rigid object cooperatively when the robots and load parameters are uncertain. We propose a controller that takes into account the dynamics of both the load and the manipulators. The linearity of the dynamics of the robots and the load, with respect to the unknown parameters, is exploited during the derivation of the parameter adaptation scheme. In order to design a control and update laws that do not require the measurements of the of the joint accelerations or the load acceleration, the dynamics of both the robots and the load are filtered through a stable first order filter. Then two prediction error vectors are defined as the difference between the measured filtered dynamics and the predicted filtered dynamics of both the robots and the load. The least-squares estimation method is used to estimate the parameters of the multi-robot system from the prediction errors. We then develop a controller that is based on the cancellation of the nonlinearities. The proposed controller guarantees global asymptotic tracking of the robot and load trajectories and also guarantees the asymptotic tracking of the internal forces trajectories

Method and apparatus for configuration control of redundant robots

A method and apparatus to control a robot or manipulator configuration over the entire motion based on augmentation of the manipulator forward kinematics is disclosed. A set of kinematic functions is defined in Cartesian or joint space to reflect the desirable configuration that will be achieved in addition to the specified end-effector motion. The user-defined kinematic functions and the end-effector Cartesian coordinates are combined to form a set of task-related configuration variables as generalized coordinates for the manipulator. A task-based adaptive scheme is then utilized to directly control the configuration variables so as to achieve tracking of some desired reference trajectories throughout the robot motion. This accomplishes the basic task of desired end-effector motion, while utilizing the redundancy to achieve any additional task through the desired time variation of the kinematic functions. The present invention can also be used for optimization of any kinematic objective function, or for satisfaction of a set of kinematic inequality constraints, as in an obstacle avoidance problem. In contrast to pseudoinverse-based methods, the configuration control scheme ensures cyclic motion of the manipulator, which is an essential requirement for repetitive operations. The control law is simple and computationally very fast, and does not require either the complex manipulator dynamic model or the complicated inverse kinematic transformation. The configuration control scheme can alternatively be implemented in joint space

Admittance-based adaptive cooperative control for multiple manipulators with output constraints

This paper proposes a novel adaptive control methodology based on the admittance model for multiple manipulators transporting a rigid object cooperatively along a predefined desired trajectory. First, an admittance model is creatively applied to generate reference trajectory online for each manipulator according to the desired path of the rigid object, which is the reference input of the controller. Then, an innovative integral barrier Lyapunov function is utilized to tackle the constraints due to the physical and environmental limits. Adaptive neural networks (NNs) are also employed to approximate the uncertainties of the manipulator dynamics. Different from the conventional NN approximation method, which is usually semiglobally uniformly ultimately bounded, a switching function is presented to guarantee the global stability of the closed loop. Finally, the simulation studies are conducted on planar two-link robot manipulators to validate the efficacy of the proposed approach