Abstract:The problem of finding an appropriate path for a mechanical arm that tries to reach a target among obstacles is one of the most important in fields of automation and robotics. It is both a classic inverse kinematics and collision detection problem. This project aimed to construct a tool to plan a path for an articulated arm through a two-dimensional environment with obstacles. The inverse kinematics problem is addressed by heuristics Bayesian particles filter, and the collision detection problem is solved using computational geometry methods for calculating the free configurations space. The proposed tool has a graphical interface with which you can get information from the designed experiments. The feasibility of this approach and its advantages in complex two-dimensional environments is shown. We proved that good results can be obtained with an appropriate selection of the parameters.
For a couple of years, all processors in modern machines are multi-core. Massively parallel architectures, so far reserved for super-computers, become now available to a broad public through hardware like the Xeon Phi or GPU cards. This architecture strategy has been commonly adopted by processor manufacturers, allowing them to stick with Moore's law. However, this new architecture implies new ways to design and implement algorithms to exploit its full potential. This is in particular true for constraint-based solvers dealing with combinatorial optimization problems. Here we propose a Parallel-Oriented Solver Language (POSL, pronounced "puzzle"), a new framework to build interconnected meta-heuristic based solvers working in parallel. The novelty of this approach lies in looking at solver as a set of components with specific goals, written in a parallel-oriented language based on operators. A major feature in POSL is the possibility to share not only information, but also behaviors, allowing solver modifications during runtime. Our framework has been designed to easily build constraint-based solvers and reduce the developing effort in the context of parallel architecture. POSL's main advantage is to allow solver designers to quickly test different heuristics and parallel communication strategies to solve combinatorial optimization problems, usually timeconsuming and very complex technically, requiring a lot of engineering.
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