This paper describes an automated sewing system that focuses on sewing of curved edge segments. The sewing cell includes an industrial sewing machine as well as three industrial robots that handle the parts during the sewing process. Based on experiences from previous work, several improvements are presented that address issues with previous implementations. The main contribution concerning the control system is a model-based generation of the feed-forward velocity for the robot tool movement, based on a geometric description of the parts. This approach increases performance, especially in the case of curved fabric, as well as robustness in case of faulty sensor data. Additionally, this paper describes hardware upgrades that address mechanical challenges that were described in former publications. Finally, the paper presents experiments comparing the model-based control approach with the former control system based on constant feed-forwards velocity and setpoints.

This paper presents a control system for fast cooperative dual-arm manipulation of rigid objects with experimental results. The motivation for multi-arm manipulation comes from the wide range of applications. The possible tasks that can be performed by such a system greatly exceed those of a single manipulator system. The proposed system is flexible with respect to uncertainties in object size. Moreover, it allows for physical human interaction through force/torque sensing. This is especially beneficial in industrial cases where humans and robots work on the same production line. One main goal of this paper is to bridge the gap between current research regarding dual-arm manipulation and the implementation possibilities on current industrial robots and widely available standard hardware.

Automated sewing is a complicated task in manufacturing. Due to the non-rigid work pieces and variations in the material characteristics, sensor-based control has to be used to accomplish the sewing operation. This paper presents a strategy for velocity synchronization and corner matching in an automated sewing cell based on two industrial manipulators and a sewing machine. A hybrid force/motion control scheme is adopted using feedback from force/torque sensors for tension control and optical sensors to control the seam position. The strategy is based on switching between force control and displacement control using a leader/follower coordination scheme. This addresses the problem of corner mismatch occurring when two independent force controllers are used for controlling the two robots. Experiments verify that the proposed method gives a satisfactory corner matching, which is crucial for the presented sewing case.

The stability of discrete time kinematic sensor-based control of robots is investigated in this paper. A hierarchical inner-loop/outer-loop control architecture common for a generic robotic system is considered. The inner loop is composed of a servo-level joint controller and higher level kinematic feedback is performed in the outer loop. Stability results derived in this paper are of interest in several applications including visual servoing problems, redundancy control, and coordination/synchronization problems. The stability of the overall system is investigated taking into account input/output delays and the inner loop dynamics. A necessary and sufficient condition that the gain of the outer feedback loop has to satisfy to ensure local stability is derived. Experiments on a Kuka K-R16 manipulator have been performed in order to validate the theoretical findings on a real robotic system and show their practical relevance.

The aim of this paper is to investigate the discrete-time stability of robot motion control in the task space. The control system has been modeled as a classical inner-loop/outer-loop architecture, adopted in several industrial robotic systems. The inner-loop is composed of a servo-level joint controller, and higher level kinematic feedback is performed in the outer-loop. Heterogeneous dynamics is considered in the inner-loop, which can for instance describe redundant coordination/synchronization control systems with cooperative robots with non-identical dynamical responses. There are surprisingly few discrete-time stability results in the current state-of-the-art for this popular control architecture. The qualitative effects of the inner-loop dynamics on the overall stability of the system is investigated, and improved outer-loop feedback gain margins are derived.

This paper presents a novel Coriolis/centripetal matrix factorization applicable to serial link rigid manipulators. The computationally efficient Coriolis matrix factorization is explicitly given as a function of the robot's kinematic matrices and their time derivatives which are easily obtained using the Denavit-Hartenberg-convention. The factorization is different from the popular Christoffel symbol representation, but the important skew-symmetry property is preserved. The proposed factorization is used to determine the class of manipulators for which a particular non-minimal representation of the manipulator dynamics exists.

In this paper, we present a solution and experimental results for real-time control of manipulation tasks considering the alignment of a robots end effector relative to some reference. The developed controller is applicable to industrial manipulators and is based on the pseudoinverse redundancy resolution method. The application considered is the employment of two industrial robots in an offshore remote inspection and maintenance system. A leader robot is controlled freely from onshore, and a follower robot uses an attached camera to provide the onshore operator with live video feed of the ongoing operation. Robot manipulators constitute flexible camera platforms, compared to e.g. simple pan/tilt units, for monitoring offshore operations. We develop a controller for the follower robot such that automatic camera tracking is achieved using pseudoinverse redundancy resolution control. A minimal task space parametrization relying on stereographic projection is constructed which achieves relative end effector alignment tracking without introducing representational or algorithmic singularities. It is shown that singular configurations will only in special cases affect the closed loop behavior. The controller is applicable to tasks such as spray painting or polishing on curved surfaces. The control approach is experimentally validated on two Kuka KR-16 industrial robot manipulators.

Remote controlled robots on offshore oil and gas platforms can potentially reduce costs and improve environment, health and safety issues. A key to successful remote control is to provide onshore operators with a sufficient overview of the processes offshore. To this end, robot manipulators constitute flexible camera platforms, compared to e.g. simple pan-tilt units, for monitoring offshore operations. In this paper, we present a system solution and experimental results for real-time active camera control with obstacle avoidance for industrial manipulators based on weighted pseudoinverse redundancy resolution method. We extend the pseudoinverse solution for joint limit avoidance in combination with obstacle avoidance such that joint limits are gracefully avoided. A novel choice of stereographic projection provides robustness with respect to global stability and singularities. Implementation issues are addressed and the monitoring approach is experimentally validated on two Kuka KR-16 robot manipulators. Experimental results show that a follower robot with a camera is able to monitor and track a leader robot while simultaneously avoiding collisions. In addition, a robot control system architecture which ensures efficient and safe testing of new Matlab-implemented robot controllers is presented.