The Wannier-Bloch resonance states are metastable states of a quantum particle in a space-periodic potential plus a homogeneous field. Here we analyze the states of quantum particle in space- and time-periodic potential. In this case the dynamics of the classical counterpart of the quantum system is either quasiregular or chaotic depending on the driving frequency. It is shown that both the quasiregular and the chaotic motion can also support quantum resonances. The relevance of the obtained result to the problem a of crystal electron under simultaneous influence of d.c. and a.c. electric fields is briefly discussed. PACS: 73.20Dx, 73.40Gk, 05.45.+b
We study the statistics of the Wigner delay time and resonance width for a Bloch particle in ac and dc fields in the regime of quantum chaos. It is shown that after appropriate rescaling the distributions of these quantities have universal character predicted by the random matrix theory of chaotic scattering.
We present a parallel path planning method that is able to automatically handle multiple goal configurations as input. There are two basic approaches, goal switching and bi-directional search, which are combined in the end. Goal switching dynamically selects a fa-vourite goal depending on some distance function. The bi-directional search supports the backward search direction from the goal to the start configuration, which is probably faster. The multi-directional search with goal switching combines the advantages of goal switching and bi-directional search. Altogether, the planning system is enabled to select one of the pref-erable goal configuration by itself. All concepts are experimentally validated for a set of benchmark problems consisting of an industrial robot arm with six degrees of freedom in a 3D environment.
Es wird die Aufgabe der vollständigen räumlichen Abdeckung von Regionen in durch mobile Roboter betrachtet. Da-bei können die Regionen in vollständig, teilweise oder nicht bekannten Umgebungen liegen. Zur Lösung wird ein Verfahren aus der Computer-grafik zum Füllen von Bildregionen zugrunde gelegt. Das Verfahren hat eine lokale Sichtweise und läßt somit den Einsatz von Sensordaten und das Auftreten von unvorhergesehenen Hindernissen zu. Die Regionen können durch Karten off-line vorgegeben sein oder durch Sensordaten on-line aufgebaut werden. Dennoch ist eine vollständige und genau einma-lige Flächenbearbeitung garantiert. Dies wird an Beispielen in einer graphischen Visualisierung der Realzeit-Steuerung des Roboters validiert.
This paper presents a new approach to parallel motion planning for industrial robot arms with six degrees of freedom in an on-line given 3D environment. The method is based on the A*-search algorithm and needs no essential off-line computations. The algorithm works in an implicitly descrete configuration space. Collisions are detected in the cartesian workspace by hierarchical distance computation based on the given CAD model. By decomposing the 6D configuration space into hypercubes and cyclically mapping them onto multiple processing units, a good load distribution can be achieved. We have implemented the parallel motion planner on a workstation cluster with 9 PCs and tested the planner for several benchmark environments. With optimal discretisation, the new approach usually shows linear, and sometimes even superlinear speedups. In on-line provided environments with static obstacles, the parallel planning times are only a few seconds.
A practical distributed planning and control system for industrial robots is presented. The hierarchical concept consists of three independent levels. Each level is modularly implemented and supplies an application interface (API) to the next higher level. At the top level, we propose an automatic motion planner. The motion planner is based on a best-first search algorithm and needs no essential off-line computations. At the middle level, we propose a PC-based robot control architecture, which can easily be adapted to any industrial kinematics and application. Based on a client/server-principle, the control unit estab-lishes an open user interface for including application specific programs. At the bottom level, we propose a flexible and modular concept for the integration of the distributed motion control units based on the CAN bus. The concept allows an on-line adaptation of the control parameters according to the robot's configuration. This implies high accuracy for the path execution and improves the overall system performance.
We present a parallel control architecture for industrial robot cells. It is based on closed functional components arranged in a flat communication hierarchy. The components may be executed by different processing elements, and each component itself may run on multiple processing elements. The system is driven by the instructions of a central cell control component. We set up necessary requirements for industrial robot cells and possible parallelization levels. These are met by the suggested robot control architecture. As an example we present a robot work cell and a component for motion planning, which fits well in this concept.
This paper is based on a path planning approach we reported earlier for industrial robot arms with 6 degrees of freedom in an on-line given 3D environment. It has on-line capabilities by searching in an implicit and descrete configuration space and detecting collisions in the Cartesian workspace by distance computation based on the given CAD model. Here, we present different methods for specifying the C-space discretization. Besides the usual uniform and heuristic discretization, we investigate two versions of an optimal discretization for an user-predefined Cartesian resolution. The different methods are experimentally evaluated. Additionally, we provide a set of 3- dimensional benchmark problems for a fair comparison of path planner. For each benchmark, the run-times of our planner are between only 3 and 100 seconds on a Pentium PC with 133 MHz.
In this paper, the problem of path planning for robot manipulators with six degrees of freedom in an on-line provided three-dimensional environment is investigated. As a basic approach, the best-first algorithm is used to search in the implicit descrete configuration space. Collisions are detected in the Cartesian workspace by hierarchical distance computation based on the given CAD model. The basic approach is extended by three simple mechanisms and results in a heuristic hierarchical search. This is done by adjusting the stepsize of the search to the distance between the robot and the obstacles. As a first step, we show encouraging experimental results with two degrees of freedom for five typical benchmark problems.