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In recent years, the avoidance strategies have become progressively more complex, yet better aligned to pilot see and avoid behaviour. Significant advances have also allowed the system to be characterised by two mutual exclusive thresholds, one for making avoidance decisions and the other for determining when to stop avoidance behaviour. The importance of this is that existing performance evaluation techniques, used to asses systems, such as TCAS, can be leveraged to simultaneously optimise system parameters, determine performance limits, and visualise design trade-offs. The evaluation framework also follows on naturally from the techniques utilising receiver operating curves used to asses the detection performance using similar techniques. [ABSTRACT FROM PUBLISHER]

This paper deals with constrained image-based visual servoing of circular and conical spiral motion about an unknown object approximating a single image point feature. Effective visual control of such trajectories has many applications for small unmanned aerial vehicles, including surveillance and inspection, forced landing (homing), and collision avoidance. A spherical camera model is used to derive a novel visual-predictive controller (VPC) using stability-based design methods for general nonlinear model-predictive control. In particular, a quasi-infinite horizon visual-predictive control scheme is derived. A terminal region, which is used as a constraint in the controller structure, can be used to guide appropriate reference image features for spiral tracking with respect to nominal stability and feasibility. Robustness properties are also discussed with respect to parameter uncertainty and additive noise. A comparison with competing visual-predictive control schemes is made, and some experimental results using a small quad rotor platform are given. [ABSTRACT FROM PUBLISHER]