An algorithm and data management scheme is presented to utilize the data output of the SR-3000, a 3D LIDAR sensor. The SR-3000 generates a 4D point cloud at video frame rates where each point is described by its 3D coordinates and its optical intensity. The implementation of each major component of the algorithm is described, including a projective ICP algorithm, reverse calibration equations for the SR-3000 sensor, the processing of the intensity data, and a point selection algorithm which includes the use of a 3D volume feature extraction algorithm. This ICP based alignment algorithm is used in the context of a data management scheme that stores and retrieves scan data and intermediate data products to realize pseudo-global scan alignment, data compression, and real time data display.

Effects-based operations have been demonstrated on hardware to realize practical and autonomously performed behaviors utilizing a variety of vehicle platforms including ground, water surface, and aerial vehicles. The heterogeneous vehicle swarms enact a variety of cooperative behaviors autonomously, using reactive, effects-based algorithms and broadcast-only, decentralized communications. Control is achieved through the use of stigmergic potential fields, a form of cooperative motor schema behavior based upon mathematical functions that are associated with entities in the operational environment of the vehicle. The video demonstration shows footage from actual hardware tests that have demonstrated empirically how reactive swarming behaviors using stigmergic potential fields can offer robustly sufficient behavior with improved total system survivability and total operational effectiveness, particularly under dynamic environmental and operational conditions.