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.
In this paper we discuss the control of cooperating tasks being done by two robotic arms. In order to control those tasks, we extend hybrid position force control scheme presented thus far by various researchers for a single-arm robot. The point of the extension is formulation of kinematics and statics for a two-arm robot which is new in this paper. We define a unique system of workspace coordinates and, corresponding to the unique workspace, introduce an unique jointspace vector consisting of joint-vectors of the two arms. Using these work and joint spaces, we formulate kinematics and statics. Based upon this formulation, we successfully apply the hybrid scheme to the two-arm robot. A demonstration of the theory working on a real two-arm industrial robot and experimental data of simultaneous control of position and force proves the effectiveness of our method. Three schemes are developed which are aimed at achieving cooperative control of multiple arm systems manipulating a common object. The first scheme operates wholly on the object task space variables. The second scheme operates on the joint space variables that can be derived via a kinematic inversion from the cooperative task space variables. The third scheme combines the features of the two by solving the cooperation at the inverse kinematic level and acting the control at the object level. Simulation results are provided for a two-arm planar system to investigate the behavior of the controlled system in the case of inaccurate object modeling. >    We propose a human-robot cooperation scheme for bimanual robots. After the initial task demonstration, the human co-worker can modify both the spatial course of motion as well as the speed of execution in an intuitive way. To achieve this goal, speed-scaled dynamic motion primitives are applied for the underlying task representation. The proposed adaptation scheme adjusts the robot's stiffness in path operational space, i. e. along the trajectory. It allows a human co-worker to be less precise in the parts of the task that require high precision, as the precision aspect can be provided by the robot. The required dynamic capabilities of the robot were obtained by decoupling the bimanual robot dynamics in operational space, which is attached to the desired trajectory. The proposed scheme was validated in a task where two Kuka LWR-4 robot arms cooperate with a human to carry an object.  A humanoid robot can be viewed as a constrained dynamic system with constraints imposed by manipulation tasks, locomotion tasks, and the environment. This paper focuses on dealing with constraints in the upper-body of humanoid robots for manipulation tasks that involve coordinated motion of two arms. Inspired by research on human bimanual actions in the biomechanics area, we have developed the Extended-Cooperative-Task-Space (ECTS) representation that efficiently describes various coordinated motion tasks performed by a humanoid robot. Furthermore, we present a general whole-body control framework as an optimal controller based on Gauss's principle of least constraint. We show that all the constraints imposed on a humanoid system can be handled in a unified manner. The proposed framework is verified by numerical simulations on a Hubo II+ humanoid robot model.  Tasks for two coordinated industrial robots always bring the robots in contact with the same object. Physically the three form a closed kinematic chain mechanism. When the chain is in motion, the positions and orientations of the two robots must satisfy a set of holonomic equality canstraints for every time instant. To eliminate motion errors between them, we assign one of them to carry the major part of the task. Its motion is planned accordingly. The motion of the second robot is to follow that of the first robot, as specified by the re lations of the joint velocities derived from the constraint conditions. Thus if any modification of the motion is needed in real time, only the motion of the first robot is modified. The modification for the second robot is done implicitly through the constraint conditions. Specifically, when the joint displacements, velocities, and accelerations of the first robot are known for the planned or modified motion, the corre sponding variables for the second robot and the for...  In this work, we address the dual-arm manipulation of a two degrees-of-freedom articulated object that consists of two rigid links. This can include a linkage constrained along two motion directions, or two objects in contact, where the contact imposes motion constraints. We formulate the problem as a cooperative task, which allows the employment of coordinated task space frameworks, thus enabling redundancy exploitation by adjusting how the task is shared by the robot arms. In addition, we propose a method that can estimate the joint location and the direction of the degrees-of-freedom, based on the contact forces and the motion constraints imposed by the object. Experimental results demonstrate the performance of the system in its ability to estimate the two degrees of freedom independently or simultaneously.  We propose the Dexterous Manipulation Graph as a tool to address in-hand manipulation and reposition an object inside a robot's end-effector. This graph is used to plan a sequence of manipulation primitives so to bring the object to the desired end pose. This sequence of primitives is translated into motions of the robot to move the object held by the end-effector. We use a dual arm robot with parallel grippers to test our method on a real system and show successful planning and execution of in-hand manipulation.