The “timed elastic band” approach optimizes robot trajectories by subsequent modification of an initial trajectory generated by a global planner. The objectives considered in the trajectory optimization include but are not limited to the overall path length, trajectory execution time, separation from obstacles, passing through intermediate way points and compliance with the robots dynamic, kinematic and geometric constraints. “Timed elastic bands” explicitly consider spatial-temporal aspects of the motion in terms of dynamic constraints such as limited robot velocities and accelerations. The trajectory planning operates in real time such that “timed elastic bands” cope with dynamic obstacles and motion constraints. The “timed elastic band problem” is formulated as a scalarized multi-objective optimization problem. Most objectives are local and relate to only a small subset of parameters as they only depend on a few consecutive robot states. This local structure results in a sparse system matrix, which allows the utilization of fast and efficient optimization techniques such as the open-source framework “g2o” for solving “timed elastic band” problems. The “g2o” sparse system solvers have been successfully applied to VSLAM problems. This contribution describes the application and adaptation of the g2o-framework in the context of trajectory modification with the “timed elastic band”. Results from simulations and experiments with a real robot demonstrate that the implementation is robust and computationally efficient.

The classic "elastic band" deforms a path generated by a global planner with respect to the shortest path length while avoiding contact with obstacles. It does not take any dynamic constraints of the underlying robot into account directly. This contribution introduces a new approach called "timed elastic band" which explicitly considers temporal aspects of the motion in terms of dynamic constraints such as limited robot velocities and accelerations. The "timed elastic band" problem is formulated in a weighted multi-objective optimization framework. Most objectives are local as they depend on a few neighboring intermediate configurations. This results in a sparse system matrix for which efficient large-scale constrained least squares optimization methods exist. Results from simulations and experiments with a real robot demonstrate that the approach is robust and computationally efficient to generate optimal robot trajectories in real time. The "timed elastic band" converts an initial path composed of a sequence of way points into a trajectory with explicit dependence on time which enables the control of the robot in real time. Due to its modular formulation the approach is easily extended to incorporate additional objectives and constraints.

Service robots serve and assist human beings sharing a common work space. Collision-free motion paths have to be generated in short times for a convenient man-machine interaction. The time for generating these paths heavily depends on the complexity of the workspaces. Workspaces might be partially known, but generally information about the workspaces is perceived by sensor systems during runtime. This work presents a motion planner interacting with reactive plan execution systems. Dividing the work space into subspaces appropriate paths are determined in split seconds. Based on an environment model collisions are avoided by interacting with an obstacle avoidance system. Tactile sensors are used to detect collisions of the robot arm, e.g. due to an incomplete knowledge of the work space or enforced by a human touching the robot. Experimental results of our 8 degree of freedom manipulator arm mounted on a mobile platform are presented. In these experiments the robot acts as a barkeeper.

In the field of service robotics, robots serve and assist human beings. Ways to interact with the robot are required. For human a natural way of interaction is by physical contact. This paper uses tactile sensors to enable this kind of interaction. Several kinds of tactile interactions between a user and the robot as well as interactions of the robot with the environment are introduced. All interactions are implemented in a single paradigm: Forces measured from tactile sensors result in motion vectors at the contact points. The motion vectors from different sensors are superimposed and then determine the robots joint velocities. Results from our experimental setup consisting of an 8 degrees of freedom manipulator arm mounted on a mobile platform are presented. In one illustrated example the robot is moved by a human using only the tactile interface. A second example shows a robot working as a barkeeper assistant. The human barkeeper works close with the robot safely.

Service robots serve and assist human beings sharing a common environment. Therefore fast responding and robust planners generating collision-free motions are required to guarantee a safe and convenient manmachine interaction. In most cases the working environment is partially known or perceived by a sensor system. To reduce planning time, this work presents a motion planner interacting with reactive plan execution systems. Dividing the work space into subspaces appropriate motion plans are determined. Based on an environment model collisions are avoided by interacting with an obstacle avoidance system. Tactile sensors are used to detect collisions of the robot arm, e.g. due to an incomplete knowledge of the environment or enforced by a human touching the robot. Experimental results of our 8 degree of freedom manipulator arm mounted on a mobile platform are presented. In these experiments the robot acts as a barkeeper.

In the field of service robotics, robots serve and assist human beings. It is natural for humans to directly interact with the robot via tactile interfaces. This paper introduces several kinds of tactile interactions between a user and the robot as well as interactions of the robot with the environment. All interactions are implemented in a single paradigm: Forces measured from tactile sensors result in motion vectors at the contact points. The motion vectors from different sensors are superimposed and then determine the robot’s joint velocities. We present results from our experimental setup consisting of an 8 degrees of freedom manipulator arm mounted on a mobile platform. In the illustrated example, a human interacts with the robot using only the tactile interface.

The first robots are currently appearing on the consumer market. Initially they are targeted at rather simple applications such as entertainment and home convenience. For more complex areas, these robots will need to collaborate and interactively communicate with their human users, which requires appropriate man-machine interaction technologies and considerable cognitive abilities on the robot's side. Consumer acceptance will strongly depend on the integrated system. Thus, system integration and evaluation of the integrated system is becoming increasingly important. This paper describes our approach to construct a robotic assistance system. We present experience with an integrated technology demonstration and exposure of the integrated system to the public.

Service robots serve and assist human beings sharing a common environment. Therefore, fast responding and robust planners generating collision-free motions are required to guarantee a safe and convenient man-machine interaction. In most cases the working environment is partially known or perceived by a sensor system. To reduce planning time, this work presents a motion planner interacting with reactive plan execution systems. By dividing the work space into subspaces appropriate motion plans are determined. Based on an environment model, collisions are avoided by interacting with an obstacle avoidance system. Tactile sensors are used to detect collisions of the robot arm, e.g. due to an incomplete knowledge of the environment or enforced by a human touching the robot. Experimental results of our 8 degree of freedom manipulator arm mounted on a mobile platform are presented. In these experiments the robot acts as a barkeeper.

In the field of service robotics, robots serve and assist human beings. It is natural for humans to directly interact with the robot via tactile interfaces. This paper introduces several kinds of tactile interactions between a user and the robot as well as interactions of the robot with the environment. All interactions are implemented in a single paradigm: Forces measured from tactile sensors result in motion vectors at the contact points. The motion vectors from different sensors are superimposed and then determine the robot's joint velocities. We present results from our experimental setup consisting of an 8 degrees of freedom manipulator arm mounted on a mobile platform. In the illustrated example, a human interacts with the robot using only the tactile interface.

Most service robots work in the same environment as humans. Therefor the robot must provide interaction channels to the human. This paper introduces a interaction via a tactile interface. Several kinds of tactile interactions between a user and the robot as well as interactions of the robot with the environment are presented. All interactions are implemented in a single paradigm: Forces measured from tactile sensors result into robot joint torques. We present results from our experimental setup. In the illustrated example, a human interacts with the robot using only the tactile interface.

Im Bereich der mobilen Servicerobotik sind Interaktionsmöglichkeiten zwischen Mensch und Maschine erwünscht, die deutlich über derzeit verfügbare hinausgehen. In diesem Beitrag werden ein Kollisionsvermeidung s system und Kontaktreflexsystem vorgestellt, die zusammen mit einer „künstlichen Haut“ die unmittelbare Interaktion im gleichen Arbeitsbereich ermöglichen. Die berührungslose und taktile Sensorik des Systems dient der Umgebungswahrnehmung und trägt darüber hinaus zur Sicherheit des Benutzers bei. Beispielhafte Ergebnisse werden mit Hilfe einer Simulation und anhand von Experimenten mit einem realen Roboter gezeigt.

Der Einsatz von mobilen Servicerobotern beschränkt sich bisher auf Transport- und Reinigungsaufgaben, bei welcher Mobilität und Navigation in einer 2-dimensionalen Welt die zentrale Rolle spielen. Weitere Einsatzgebiete (z.B. im Haushalt) erfordern die Fähigkeit, Gegenstände manipulieren zu können. Inhalt dieses Beitrages ist die Beschreibung des bei der Siemens AG hierfür entwickelten Forschungsprototypen für Mobilität und Manipulation (MobMan) in Alltagsumgebungen. Der Schwerpunkt liegt auf einem Ansatz zur Steuerung von Manipulationsskills in komplexen Alltagsumgebungen.