A Research Of Simulation Key Technologies For Autonmous Navigation Robot

Autonomous robotic technology is wildly used in defense, civil economy and academic researches. As a research combined with image processing, data collection, data fusion, intelligent sensor, pattern recognition, automatic control and system simulation technologies, autonomous robotic technology is one of the hottest areas in computer science. Virtual simulation system as one strong support for intelligent sensor and path land modular is a key technology of autonomous robotic researches.This thesis is focus on technologies which is needed for construct the autonomous robot virtual simulation system. Our researches is based on computer graphic and virtual reality technology to development researches on terrain rendering, sensor simulation, and the construction of virtual experiment environments. The results include:To solve the outdoor rendering problems, we proposed a GPU-implemented quad-tree based terrain rendering scheme, increasing the speed of quad-tree construction by exploit the stream-structure of GPU. Base on the scheme, we propose GPU-implemented quad-tree traversing, scene division, crack fixing and triangulation schemes, to rendering the DEM, with good rendering results and frame rates. Moreover, by introducing the clipmap technology which is widely used in large scale scene rendering into quad-tree construction, we proposed a set of technology including crack fix strategy, data management scheme and rendering optimization strategy to solve the terrain rendering of large scale scene. The experiments prove that our scheme combined with the advantages of dynamic construction algorithm and fix mesh algorithm, need no preprocessing, lightly reliance to runtime data transmission, with little bandwidth consumption. The experiments also show that our scheme could reach high frame rates with low CPU payload.To satisfy the need of sensor simulation, this thesis has also proposed technologies for laser radar and optical camera simulation, which are the most popular sensors on autonomous robot, by exploiting environment texture and bump map features of GPU. The experiment of laser radar simulation shows that our algorithm is efficient for most radar type, with a satisfactory simulation speed, while the experiment of optical camera show that the virtual camera could build relationship with real camera with high reality, also could it simulate various lens distortions. As our method fully consider about the GPU architechture, it could not only reach very high frame rates in ordinary desktop platform, but also reduce the usage of bandwidth and payload of CPU. This thesis also presented our researches on virtual experiment environment construction with sensor on autonomous robot. One is construction of polygon environment with laser radar. With a scheme of polygon linkage, mesh simplification to construct the polygon meshes the experiments needed. Experiments show that our mesh simplification strategy could largely reduce the redundant polygons while maintaining the geometry feature of existing meshes, and with good halting strategies. The second is technology of constructing outdoor environment's DEM data by data fusion with laser radar and height field data from optical cameras and a set of operation such as smoothing and blank area filling. Experiment show that our method was simple and efficient, and good at blank area filling.