164,929 research outputs found
Using Component-based Software Synthesis and Constraint Solving to generate Sets of Manufacturing Simulation Models
There is a high degree of flexibility in the design of production systems when it comes to the selection and configuration of machines. Simulation supports this complex decision process. However, modeling various configurations in a simulation environment is very time-consuming. We present a framework that includes component-based software synthesis to generate the set of all possible simulation models for the respective planning case. From the set, feasible solutions for a simulation study are then selected using constraint solving methods. We evaluate our approach using a practical example from sheet metal production
k-Color Multi-Robot Motion Planning
We present a simple and natural extension of the multi-robot motion planning
problem where the robots are partitioned into groups (colors), such that in
each group the robots are interchangeable. Every robot is no longer required to
move to a specific target, but rather to some target placement that is assigned
to its group. We call this problem k-color multi-robot motion planning and
provide a sampling-based algorithm specifically designed for solving it. At the
heart of the algorithm is a novel technique where the k-color problem is
reduced to several discrete multi-robot motion planning problems. These
reductions amplify basic samples into massive collections of free placements
and paths for the robots. We demonstrate the performance of the algorithm by an
implementation for the case of disc robots and polygonal robots translating in
the plane. We show that the algorithm successfully and efficiently copes with a
variety of challenging scenarios, involving many robots, while a simplified
version of this algorithm, that can be viewed as an extension of a prevalent
sampling-based algorithm for the k-color case, fails even on simple scenarios.
Interestingly, our algorithm outperforms a well established implementation of
PRM for the standard multi-robot problem, in which each robot has a distinct
color.Comment: 2
Efficient Multi-Robot Motion Planning for Unlabeled Discs in Simple Polygons
We consider the following motion-planning problem: we are given unit
discs in a simple polygon with vertices, each at their own start position,
and we want to move the discs to a given set of target positions. Contrary
to the standard (labeled) version of the problem, each disc is allowed to be
moved to any target position, as long as in the end every target position is
occupied. We show that this unlabeled version of the problem can be solved in
time, assuming that the start and target positions are at
least some minimal distance from each other. This is in sharp contrast to the
standard (labeled) and more general multi-robot motion-planning problem for
discs moving in a simple polygon, which is known to be strongly NP-hard
A Certified-Complete Bimanual Manipulation Planner
Planning motions for two robot arms to move an object collaboratively is a
difficult problem, mainly because of the closed-chain constraint, which arises
whenever two robot hands simultaneously grasp a single rigid object. In this
paper, we propose a manipulation planning algorithm to bring an object from an
initial stable placement (position and orientation of the object on the support
surface) towards a goal stable placement. The key specificity of our algorithm
is that it is certified-complete: for a given object and a given environment,
we provide a certificate that the algorithm will find a solution to any
bimanual manipulation query in that environment whenever one exists. Moreover,
the certificate is constructive: at run-time, it can be used to quickly find a
solution to a given query. The algorithm is tested in software and hardware on
a number of large pieces of furniture.Comment: 12 pages, 7 figures, 1 tabl
Integrated Environmental Process Planning for the Design & Manufacture of Automotive Components
Advanced Product Quality Planning (APQP) logic is widely used by manufacturers for
the design and manufacture of automotive components. Manufacturers are increasingly
finding difficulties to incorporate environmental considerations in the broad range of
products that they manufacture. Therefore, there is a need for a systematic method for
environmental process planning to evaluate product configurations and their associated
environmental impact. The framework and models discussed in this paper can deal with
a variety of product characteristics and environmental impacts through a selection of
Environmental Performance Indicators (EPIs) for a final product configuration. The
framework and models have been applied in a real-life application and have proven that
changes in product design or process selection can reduce the product's environmental
impact and increase process efficiency. Hence, manufacturers can use the framework
and models during the Advanced Product Quality Planning (APQP) process to
benchmark each product variation that they manufacture in a standardised manner and
realise cost saving opportunities
Progressive Reliability Method and Its Application to Offshore Mooring Systems
Assessing the reliability of complex systems (e.g. structures) is essential for a reliability-based optimal design that balances safety and costs of such systems. This paper proposes the Progressive Reliability Method (PRM) for the quantification of the reliability of complex systems. The proposed method is a closed-form solution for calculating the probability of failure. The new method is flexible to the definition of “failure” (i.e., can consider serviceability and ultimate-strength failures) and uses the rules of probability theory to estimate the failure probability of the system or its components. The method is first discussed in general and then illustrated in two examples, including a case study to find the safest configuration and orientation of a 12-line offshore mooring system. The PRM results are compared with results of a similar assessment based on the Monte Carlo simulations. It is shown in the example of two-component that using PRM, the importance of system components to system safety can be quantified and compared as input information for maintenance planning
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