Training and optimization of operating parameters for flash LADAR cameras

Flash LADAR cameras based on continuous-wave, time-of-flight range measurement deliver fast 3D imaging for robot applications including mapping, localization, obstacle detection and object recognition. The accuracy of the range values produced depends on characteristics of the scene as well as dynamically adjustable operating parameters of the cameras. In order to optimally set these parameters during camera operation we have devised and implemented an optimization algorithm in a modular, extensible architecture for real-time applications including robot control. The approach uses two components: offline nonlinear optimization to minimize the range error for a training set of simple scenes followed by an online, real-time algorithm to reference the training data and set camera parameters. We quantify the effectiveness of our approach and highlight topics of interest for future research.