Isaac SDK and Sim tools produced by NVIDIA have great potential in assisting, accelerating and even enabling, in some cases, the development of robotic applications that make use of some sort of artificial intelligence technique. This tutorial intends to show to its audience a quick theoretical background, the whole setting up process of such tools, how to integrate it to a powerful embedded system, the Jetson Nano, and a number of examples of current applications together with a good portion of possibilities enabled by those tools.

No abstract

No abstract

No abstract

Meshless methods to simulate fluid flows have been increasingly evolving through the years since they are a great alternative to deal with large deformations, which is where meshbased methods fail to perform efficiently. A well known meshless method is the Moving Particle Semi-implicit (MPS) method, which was designed to simulate free-surface truly incompressible fluid flows. Many variations and refinements of the method’s accuracy and precision have been proposed through the years and, in this paper, a reasonably wide literature review was performed together with their theoretical and mathematical explanations. Due to these works, it has proved to be very useful in a wide range of naval and mechanical engineering problems. However, one of its drawbacks is a high computational load and some quite time-consuming functions, which prevents it to be more used in Computer Graphics and Virtual Reality applications. Graphics Processing Units (GPU) provide unprecedented capabilities for scientific computations. To promote the GPU-acceleration, the solution of the Poisson Pressure equation was brought into focus. This work benefits from some of the techniques presented in the related work and also from the CUDA language in order to get a stable, accurate and GPU-accelerated MPS-based method, which is this work’s main contribution. It is shown that the GPU version of the method developed can perform from, approximately, 6 to 10 times faster with the same reliability as the CPU version, both extended to three dimensions. Lastly, a simulation containing a total of 62,600 particles is fully rendered in 3D.