Measurement data supplementation of shadow casted image processing methods

Recently, planetary surface surface exploration based on robotic technology such as a rover have huge qualitative changes on its observation quality against conventional orbital survey. One of main mission is a scientific exploration in which it will collect and observe geological samples and data. In its observation purpose, a manipulator is mounted on a rover to collect rocks and sands, and 3D surface measurement is one of key technologies to support its autonomous functions. One of the strongest candidate sensor is mono or stereo camera for its measurement. However, it is sensitive to changes in ambient light intensity and optical conditions, and it is prone to have false template-matching in a natural environment which has high similarity on its textures. In this paper, a clear boundary of shadow in space is focused as a scanning line like in LRF or an matching feature, and then SRF and SCS were introduced as robust and accurate method by using a shadow casted on work space. After discussion about error sensitivity analyses for SRF and SCS, data supplementing system is discussed and proposed. Finally, experimental evaluation is conducted by using newly developed data supplementing system on a micro rover testbed “Micro6”. More accurate, robust and wider measured data was successfully obtained in the experiment. Its results indicated much possibility on our method and system.