Choosing the best path during unmanned air vehicle （UAV） flying is the target of the UAV mission planning problem. Because of its nearly constant flight height, the UAV mission planning problem can be treated as a 2-D （horizontal） path arrangement problem. By modeling the antiaircraft threat, the UAV mission planning can be mapped to the traveling seaman problem （TSP）. A new algorithm is presented to solve the TSP. The algorithm combines the traditional ant colony system （ACS） with particle swarm optimization （PSO）, thus being called the AC-PSO algorithm. It uses one by one tour building strategy like ACS to determine that the target point can be chosen like PSO. Experiments show that AC-PSO synthesizes both ACS and PSO and obtains excellent solution of the UAV mission planning with a higher accuracy.
A novel volumetric three-dimensional（3-D） display system is developed based on the human eye persistence and the system fuses a time-series of image slices into a single hologram like 3-D aerial image. The system design is introduced and key components are described. Experimental results show that the 3-D system can guide people freely walk around the display to inspect the true 3-D image without goggles.
