Michael Schluse

Control by 3d simulation --- a new erobotics approach to control design in automation

This paper introduces new so-called control by 3D simulation concepts which are the basis for the simulation based development of complex control algorithms e. g. in the field of robotics and automation. Now, a controller design can be developed, parameterized, tested and verified using so called Virtual Testbeds until they perform adequately in simulation. Then a stripped down version of the same simulation system uses the same simulation model and the same simulation algorithms on the real hardware implementing a real-time capable controller. This results in an integrated development approach, which brings simulation technology on the real hardware to bridge the gap between simulation and real world operation. In this way, Virtual Testbeds and control by 3D simulation provide major building blocks in the emerging field of eRobotics to keep manageable the ever increasing complexity of current computer-aided solutions.

Simulation in the woods: from remote sensing based data acquisition and processing to various simulation applications

This paper focuses on joint work towards the development of simulation applications in the forest sector. They are based on advanced “semantic” world modeling techniques which use remote sensing data and processing algorithms to derive tree species classification maps, as well as forest stand attributes and single tree databases over large areas. The resulting databases are the basis for a variety of different simulation applications in an integrated system approach. Forest growth simulations aim to predict the appearance of the forest in the next decades. Forest machine simulators allow for an efficient development of forest machines and their control algorithms, as well as for cost-effective driver training. Harvesting cost simulations calculate the harvesting costs long before the lumbermen start to work. Decision support systems enable wood owners and the wood industry to compare different treatment scenarios based on simulations and thus to comprehensively assess ecological and economical chances and consequences.

Database-driven distributed 3D simulation

Distributed 3D simulations are used in various fields of application like geo information systems (GIS), space robotics or industrial automation. We present a new database-driven approach that combines 3D real-time simulation techniques with object-oriented data management. It consists of simulation clients that replicate from a central database object data as well as the data schema itself. The central database stores static and dynamic parts of a simulation model, distributes changes caused by the simulation, and logs the simulation run. Compared to standard decentralized methods this approach has several advantages like persistence for state and course of time, object identification, standardized interfaces for simulation, modeling and evaluation, as well as a consistent data schema and world model for the overall system, which at the same time serves as a means for communication.

Dynamic collision avoidance for redundant multi-robot systems

This paper presents a new approach to the online planning of collision-free robot motions and evasive actions for redundant multi-robot/multi-obstacle environments. The approach, based on the collision avoidance methodology CARE (collision avoidance in real-time environments) presented by Rossmann (1993), is a local planning approach which considers the shortest distance and relative velocity between objects. This results in an intuitively comprehensible model to determine the potential collision and provides the basis of a new way of treating collision free path-planning as an optimization problem. This optimization problem is solved in real-time and provides a mathematically exact solution of the path-planning problem by considering all the static and dynamic obstacles in the environment.

State oriented modeling as enabling technology for projective virtual reality

This paper introduces the use of supervisory control techniques for the realization of a new kind of intuitive man machine interfaces for complex automation systems. Such comprehensive user interfaces combine for the first time intuitive commanding capabilities: clear and vivid visualization of the system state as well as interactive training environments especially for the commanding of autonomous robotic systems over long distances. To achieve this, a state oriented modeling technique has been developed. It serves as an object oriented supervisory control framework and was integrated in the IRFs VR-system COSIMIR/sup (R)/ VR.

Close to Reality Simulation of Bulk Solids Using a Kind of 3D Cellular Automaton

The development of algorithms providing a close to reality simulation of dynamic virtual worlds made substantial technological progresses during the last decade — contrary to the close to reality simulation of bulk solids. Standard simulation methods like particle or rigid-body simulation are not applicable to this simulation problem because a large number of elements is needed for convincing simulation results which cannot be handled in real-time. In this paper we present a kind of 3-dimensional cellular automaton which can handle a large number of elements at the cost of a spatial discretization. This approach is combined with state of the art rigid body simulation techniques resulting in a close to reality simulation of bulk solids in real-time applications.Copyright

Integrating semantic world modeling, 3D-simulation, Virtual Reality and remote sensing techniques for a new class of interactive GIS-based simulation systems

Integrating well known GIS functionalities, object-oriented modeling, 3D simulation, Virtual Reality, space robotics and remote sensing methods with new semantic world modeling techniques, from the point of view of an industrial automation and 3D simulation expert, leads to a new approach to GIS.

Projective virtual reality in space applications: a telerobotic ground station for a space mission

Commanding complex robotic systems over long distances in an intuitive manner requires new techniques of man-machine- interaction. A first disadvantage of conventional approaches is that the user has to be a robotic expert because he directly has to command the robots. He often is part of the real-time control loop while moving the robot and thus has to cope with long delays. Experience with space robot missions showed that it is very difficult to control a robot just by camera images. At the IRF, a new approach to overcome such problems was developed. By means of Projective Virtual Reality, we introduce a new, intuitive way of man-machine communication based on a combination of action planning and Virtual Reality methods. Using data-helmet and data-glove the user can immerse into the virtual world and interact with the virtual objects as he would do in reality. The Virtual Reality System derives the users intention from his actions and then projects the tasks in to the physical world by means of robots. The robots carry out the action physically that is equivalent to the users action in the virtual world. The developed Projective Virtual Reality System is of especially great use for space applications. During the joint project GETEX (German ETS-VII Experiment), the IRF realized the telerobotic ground station for the free flying robot ERA on board the Japanese satellite ETS-VII. During the mission in April 1999 the Virtual Reality based command interface turned out to be an ideally suited platform for the intuitive commanding and supervision of the robot in space. During the mission, it first had to be verified that the system is fully operational, but then out Japanese colleagues allowed to take the full control over the real robot by the Projective Virtual Reality System. The final paper will describe key issues of this approach and the results and experiences gained during the GETEX mission.

Real-time collision avoidance in space: the GETEX experiment

Intelligent autonomous robotic systems require efficient safety components to assure system reliability during the entire operation. Especially if commanded over long distances, the robotic system must be able to guarantee the planning of safe and collision free movements independently. Therefore the IRF developed a new collision avoidance methodology satisfying the needs of autonomous safety systems considering the dynamics of the robots to protect. To do this, the collision avoidance system cyclically calculates the actual collision danger of the robots with respect to all static and dynamic obstacles in the environment. If a robot gets in collision danger the methodology immediately starts an evasive action to avoid the collision and guides the robot around the obstacle to its target position. This evasive action is calculated in real-time in a mathematically exact way by solving a quadratic convex optimization problem. The secondary conditions of this optimization problem include the potential collision danger of the robots kinematic chain including all temporarily attached grippers and objects and the dynamic constraints of the robots. The result of the optimization procedure are joint accelerations to apply to prevent the robot from colliding and to guide it to its target position. This methodology has been tested very successfully during the Japanese/German space robot project GETEX in April 1999. During the mission, the collision avoidance system successfully protected the free flying Japanese robot ERA on board the satellite ETS-VII at all times. The experiments showed, that the developed system is fully capable of ensuring the safety of such autonomous robotic systems by actively preventing collisions and generating evasive actions in cases of collision danger.

Using supervisory control methods for model based control of multi-agent systems

The development of control systems for multiple cooperating robot manipulators with redundant kinematics is still a demanding task. This task becomes even more challenging if the robots to be controlled operate in at least partly unknown environments which vary over time and which may be thousands of kilometers away from the operator, for example in space. To solve this task, the Institute of Robotics Research (IRF) combines supervisory control methods in the form of the newly developed state oriented modeling methodology with latest robot simulation technology, realizing an absolutely new approach for robot control purposes. This approach regards the robots manipulators from a discrete event system point of view. Using the state oriented modeling methodology, supervisors and controllers for those systems can be developed in a nearly intuitive way resulting in robust, fault-tolerant robot controllers. Using 3D simulation technology for model based robot control, the robot controller knows not only its own kinematic chain but also all the objects in its environment. This simplifies the task of object oriented robot programming, sensor information processing, environment model update, etc. once more. On the other hand, this allows for a smooth transition from robot simulation to robot control, because the same algorithms simulate the virtual and control the physical robots.