INTELLIGENT CONTROLLING THE GRIPPING FORCE OF AN OBJECT BY TWO COMPUTER-CONTROLLED COOPERATIVE ROBOTS

This paper presents a Multiple Adaptive Neuro-Fuzzy Inference System (MANFIS)-based method for regulating the handling force of a common object. The foundation of this method is the prediction of the inverse dynamics of a cooperative robotic system made up of two 3-DOF robotic manipulators. Considering the no slip in contact between the tool and the object, an object is moved. to create and feed the MANFIS database, the inverse kinematics and dynamic equations of motion for the closed chain of motion for both arms are established in Matlab. Results from a SimMechanic simulation are given to demonstrate how well the suggested ANFIS controller works. Several manipulated object movements covering the shared workspace of the two manipulator arms are used to test the proposed control strategy

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

The KALI multi-arm robot programming and control environment

The KALI distributed robot programming and control environment is described within the context of its use in the Jet Propulsion Laboratory (JPL) telerobot project. The purpose of KALI is to provide a flexible robot programming and control environment for coordinated multi-arm robots. Flexibility, both in hardware configuration and software, is desired so that it can be easily modified to test various concepts in robot programming and control, e.g., multi-arm control, force control, sensor integration, teleoperation, and shared control. In the programming environment, user programs written in the C programming language describe trajectories for multiple coordinated manipulators with the aid of KALI function libraries. A system of multiple coordinated manipulators is considered within the programming environment as one motion system. The user plans the trajectory of one controlled Cartesian frame associated with a motion system and describes the positions of the manipulators with respect to that frame. Smooth Cartesian trajectories are achieved through a blending of successive path segments. The manipulator and load dynamics are considered during trajectory generation so that given interface force limits are not exceeded

Experiments in cooperative manipulation: A system perspective

In addition to cooperative dynamic control, the system incorporates real time vision feedback, a novel programming technique, and a graphical high level user interface. By focusing on the vertical integration problem, not only these subsystems are examined, but also their interfaces and interactions. The control system implements a multi-level hierarchical structure; the techniques developed for operator input, strategic command, and cooperative dynamic control are presented. At the highest level, a mouse-based graphical user interface allows an operator to direct the activities of the system. Strategic command is provided by a table-driven finite state machine; this methodology provides a powerful yet flexible technique for managing the concurrent system interactions. The dynamic controller implements object impedance control; an extension of Nevill Hogan's impedance control concept to cooperative arm manipulation of a single object. Experimental results are presented, showing the system locating and identifying a moving object catching it, and performing a simple cooperative assembly. Results from dynamic control experiments are also presented, showing the controller's excellent dynamic trajectory tracking performance, while also permitting control of environmental contact force

Research and development at ORNL/CESAR towards cooperating robotic systems for hazardous environments

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of position and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace

Asymmetric Dual-Arm Task Execution using an Extended Relative Jacobian

Coordinated dual-arm manipulation tasks can be broadly characterized as possessing absolute and relative motion components. Relative motion tasks, in particular, are inherently redundant in the way they can be distributed between end-effectors. In this work, we analyse cooperative manipulation in terms of the asymmetric resolution of relative motion tasks. We discuss how existing approaches enable the asymmetric execution of a relative motion task, and show how an asymmetric relative motion space can be defined. We leverage this result to propose an extended relative Jacobian to model the cooperative system, which allows a user to set a concrete degree of asymmetry in the task execution. This is achieved without the need for prescribing an absolute motion target. Instead, the absolute motion remains available as a functional redundancy to the system. We illustrate the properties of our proposed Jacobian through numerical simulations of a novel differential Inverse Kinematics algorithm.Comment: Accepted for presentation at ISRR19. 16 Page