Grasping objects is a well-known problem in robotics. If the objects to be grasped are known, usually they are to be placed at a desired position in a desired orientation. Therefore, the object pose w.r.t the gripper has to be known before placing the object. In this paper we propose a simple and efficient, yet robust approach to this challenge, which can (nearly) eliminate dead times of the employed manipulator - hence speeding up the process significantly. Our approach is based on the observation that the problem of finding a pose at which the object can be grasped and the problem of computing the pose of the object w.r.t. the gripper can be solved separately at different stages. Special attention is paid to the popular bin-picking problem where this strategy shows its full potential. To reduce the overall cycle time, we estimate the grasp pose after the object has been grasped. Our estimation technique relies on the inertial parameters of the object - instead of visual features - which enables us to easily incorporate pose changes due to grasping. Experiments show that our approach is fast and accurate. Furthermore, it can be implemented easily and adapted to diverse pick and place tasks with arbitrary objects.

Manipulation Primitives are state-of-the-art for describing and performing complex manipulation tasks - especially in industrial applications. They combine easy task specification and execution which are key components for the success of this paradigm. However, there are some flaws when describing a complex task by decomposing it into Manipulation Primitives. For instance, the relations between the individual Manipulation Primitives cannot be captured by the original definition but have to be defined in additional glue code. This contribution introduces an extended definition of Manipulation Primitives to describe manipulation tasks as hierarchical structures using Manipulation Primitives at each level of the hierarchy. Additionally, a concept for a generic control architecture is presented which is capable of meeting the requirements of the extended Manipulation Primitive concept and which can be easily plugged“ together using modular code blocks.”

Teleoperation has a long history in the robotics community and numerous bilateral teleoperation systems employing manipulators have been proposed in the literature. On the one hand, systems have been designed which employ commercial hardware and hence generally suffer from low update rates and high delays due to restrictions of commercial manipulator controllers and haptic device controllers. On the other hand, bilateral teleoperation systems designed by research institutions often provide only few degrees of freedom. Our 6DoF bilateral teleoperation system, however, combines the amenities of commercial hardware with a high performance distributed control architecture which enables us to achieve update rates of more than 2 kHz and delays in the range of only 100 ¿s. This paper focuses on the architecture of our system and demonstrates how to achieve this performance using commercial hardware. Moreover, we show why update rates of more than 1 kHz are essential for certain teleoperation tasks. Especially with high approach velocities and stiff environments, high update rates and low delays are key requirements for stability and thus for realistic haptic perception. We present experimental results demonstrating the influence of the update rate on system stability. These results not only highlight the benefits of high update rates but also give hints on how to estimate the update rate necessary to achieve stable teleoperation for a given environment stiffness.