This paper deals with the problem of picking-up deformable linear workpieces such as cables or ropes with an industrial robot. First, we give a motivation and problem definition. Based on a brief conceptual discussion of possible approaches we derive an algorithm for picking-up hanging deformable linear objects using two light barriers as sensor system. For this hardware, a skill-based approach is described and the parameters and major influence factors are discussed. In an experi- mental study, the feasibility and reliability under diverse conditions are investigated. The algorithm is found to be very reliable, if certain boundary conditions are met.
In this paper, we investigate the efficient simulation of deformable linear objects. Based on the state of the art, we extend the principle of minimizing the potential energy by considering plastic deformation and describe a novel approach for treating workpiece dynamics. The major influence factors on precision and computation time are identified and investigated experimentally. Finally, we discuss the usage of parallel processing in order to reduce the computation time.
Enhancing the quality of surgical interventions is one of the main goals of surgical robotics. Thus we have devised a surgical robotic system for maxillofacial surgery which can be used as an intelligent intraoperative surgical tool. Up to now a surgeon preoperatively plans an intervention by studying twodimensional X-rays, thus neglecting the third dimension. In course of the special research programme "Computer and Sensor Aided Surgery" a planning system has been developed at our institute, which allows the surgeon to plan an operation on a threedimensional computer model of the patient . Transposing the preoperatively planned bone cuts, bore holes, cavities, and milled surfaces during surgery still proves to be a problem, as no adequate means are at hand: the actual performance of the surgical intervention and the surgical outcome solely depend on the experience and the skill of the operating surgeon. In this paper we present our approach of a surgical robotic system to be used in maxillofacial surgery. Special stress is being laid upon the modelling of the environment in the operating theatre and the motion planning of our surgical robot .
This paper presents fill algorithms for boundary-defined regions in raster graphics. The algorithms require only a constant size working memory. The methods presented are based on the so-called "seed fill" algorithms using the internal connectivity of the region with a given inner point. Basic methods as well as additional heuristics for speeding up the algorithm are described and verified. For different classes of regions, the time complexity of the algorithms is compared using empirical results.
Four different initialization methods for parallel Branch-and-bound algorithms are described and compared with reference to several criteria. A formal analysis of their idle times and efficiency follows. It indicates that the efficiency of three methods depends on the branching factor of the search tree. Furthermore, the fourth method offers the best efficiency of the overall algorithm when a centralized OPEN set is used. Experimental results by a PRAM simulation support these statements.
One of the many features needed to support the activities of autonomous systems is the ability of motion planning. It enables robots to move in their environment securely and to accomplish given tasks. Unfortunately, the control loop comprising sensing, planning, and acting has not yet been closed for robots in dynamic environments. One reason involves the long execution times of the motion planning component. A solution for this problem is offered by the use of highly computational parallelism. Thus, an important task is the parallelization of existing motion planning algorithms for robots so that they are suitable for highly computational parallelism. In several cases, completely new algorithms have to be designed, so that a parallelization is feasible. In this survey, we review recent approaches to motion planning using parallel computation.
For the online collision detection with a multi-arm robot a fast method for computing the so-called collision vector is presented. Manipulators and obstacles are modelled by sets of convex polytopes. Known distance algorithms serve as a foundation. To speed up the collision detection dynamic obstacles are approximated by geometric primitives and organized in hierarchies. On-line, the here introduced Dynamic Hierarchies are adjusted to the current arm configuration. A comparison with previous methods shows an increased acceleration of the computations.
A new problem for the automated off-line programming of industrial robot application is investigated. The Multi-Goal Path Planning is to find the collision-free path connecting a set of goal poses and minimizing e.g. the total path length. Our solution is based on an earlier reported path planner for industrial robot arms with 6 degrees-of-freedom in an on-line given 3D environment. To control the path planner, four different goal selection methods are introduced and compared. While the Random and the Nearest Pair Selection methods can be used with any path planner, the Nearest Goal and the Adaptive Pair Selection method are favorable for our planner. With the latter two goal selection methods, the Multi-Goal Path Planning task can be significantly accelerated, because they are able to automatically solve the simplest path planning problems first. Summarizing, compared to Random or Nearest Pair Selection, this new Multi-Goal Path Planning approach results in a further cost reduction of the programming phase.
One of the many features needed to support the activities of autonomous systems is the ability of motion planning. It enables robots to move in their environment securely and to accomplish given tasks. Unfortunately, the control loop comprising sensing, planning, and acting has not yet been closed for robots in dynamic environments. One reason involves the long execution times of the motion planning component. A solution for this problem is offered by the use of highly computational parallelism. Thus, an important task is the parallelization of existing motion planning algorithms for robots so that they are suitable for highly computational parallelism. In several cases, completely new algorithms have to be designed, so that a parallelization is feasible. In this survey, we review recent approaches to motion planning using parallel computation. As a classification scheme, we use the structure given by the different approaches to the robot's motion planning. For each approach, the available parallel processing methods are discussed. Each approach is uniquely assigned a class. Finally, for each referenced research work, a list of keywords is given.