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A pilot support system performing navigation and control tasks to guide the helicopter autonomously along a flight track based on visual machine perception is currently under development at UBM. The machine perception system uses conventional measurement data as well as CCD image sequences for state estimation, landmark I landing site recognition and tracking. The state estimates are used by a control module to perform the given guidance task. Before real flight tests can be undertaken, intensive testing and optimization of the algorithms is required; this is performed through simulation. The simulation environment allows real-time performance regarding helicopter dynamics, sensor data communication to the machine perception system, control output computation and perspectively mapped synthetic computer images representing the external world.The paper describes the simulation environment for real-time hardware-in-the-loop simulations. As many real hardware components to be used in real flight tests as possible are included within the test environment. The machine perception systern design to perform sensor fusion for ego-state estimation is presented; data interfaces to the simulation environment are discussed. A combined feedback I feedforward command generation control module uses the state estimates for guidance along the planned flight trajectory. Results from real-time simulation runs using simulation data for 'ground truth' are described.

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