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. 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.
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.
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.
Due to continuously increasing demands in the area of advanced robot control, it became necessary to speed up the computation. One way to reduce the computation time is to distribute the computation onto several processing units. In this survey we present different approaches to parallel computation of robot kinematics and Jacobian. Thereby, we discuss both the forward and the reverse problem. We introduce a classification scheme and classify the references by this scheme.
The task of handling non-rigid one-dimensional objects by a robot manipulation system is investigated. To distinguish between different non-rigid object behaviors, five classes of deformable objects from a robotic point of view are proposed. Additionally, an enumeration of all possible contact states of one-dimensional objects with polyhedral obstacles is provided. Finally, the qualitative motion behavior of linear objects is analyzed for stable point contacts. Experiments with different materials validate the analytical results.