4 research outputs found

    Randomized parallel motion planning for robot manipulators

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    We present a novel approach to parallel motion planning for robot manipulators in 3D workspaces. The approach is based on a randomized parallel search algorithm and focuses on solving the path planning problem for industrial robot arms working in a reasonably cluttered workspace.The path planning system works in the discretized configuration space, which needs not to be represented explicitly. The parallel search is conducted by a number of rule-based sequential search processes, which work to find a path connecting the initial configuration to the goal via a number of randomly generated subgoal configurations. Since the planning performs only on-line collision tests with proper proximity information without using pre-computed information, the approach is suitable for planning problems with multirobot or dynamic environments. The implementation has been carried out on the parallel virtual machine (PVM) of a cluster of SUN4 workstations and SGI machines. The experimental results have shown that the approach works well for a 6-dof robot arm in a reasonably cluttered environment, and that parallel computation increases the efficiency of motion planning significantly

    Physics Days 2018 21.3- 23.3.2018 Turku, Finland : FP2018 Proceedings

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    PhysioSim – A Full Hard- And Software Physiological Simulation Environment Applying A Hybrid Approach Based On Hierarchical Modeling Using Algebraic And Differential Systems and Dynamic Bayesian Networks

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    A system for physiological modeling and simulation is presented. The architecture is considering hardware and software support for real-time physiological simulators, which are very important for medical education and risk management. In contrary to other modeling methods, in this work the focus is to provide maximal modeling flexibility and extensibility. This is provided on the one hand by a hierarchical modeling notation in XML and on other hand by extending current methods by dynamic stochastic system modeling. Dynamic Bayesian Networks as well as deterministic system modeling by systems of algebraic and differential equations lead towards a sophisticated environment for medical simulation. Specific simulations of haemodynamics and physiological based pharmacokinetics and pharmacodynamics are performed by the proposed methods, demonstrating the applicability of the approaches. In contrary to physiological modeling and analysis tools, for an educational simulator, the models have to be computed in real-time, which requires extensive design of the hardware and software architecture. For this purpose generic and extensible frameworks have been suggested and realized. All the components together lead to a novel physiological simulator environment, including a dummy, which emulates ECG, SaO2 and IBP vital signals in addition to software signal simulation. The modeling approaches with DBN are furthermore analyzed in the domains of psychological and physiological reasoning, which should be integrated into a common basis for medical consideration. Furthermore the system is used to show new concepts for dependable medical data monitoring, which are strongly related to physiological and psychological simulations
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