Automated Model-Based Sensor Planning

点击翻译按钮获取中文摘要

9311877 Allen This is the first year of a three-year continuing award. The research focuses on strategies for automatically determining sensor parameter values for planning of sensor tasks. This will enable value selection and tailoring to match task requirements, thereby supporting more flexible and reliable autonomous operation of sensor systems. Building on a Machine Vision Planning system (MVP) already implemented at Columbia University, the new research will extend this framework, and support experiments with the system in static and dynamic environments. Three main thrusts of the research are: 1) improving the performance of the optimization approach to finding admissible viewpoints; 2) extending static sensor planning results to dynamic environments;and 3) extending MVP to sensor systems other than vision (tactile, range, and proximity).