To enable floating robots to autonomously reach for a target position while avoiding obstacles we have generalized the attractor dynamics approach established for wheeled mobile robots to motion generation in blimps or lighter-than-air vehicles. In this approach the level of modelling is at the level of behaviours. A “dynamics'' of behaviour is defined over a state space of behavioural variables (heading direction, forward velocity and altitude). The environment is also modelled in these terms by representing task constraints as attractors (i.e. asymptotically stable states) or reppelers (i.e. unstable states) of behavioural dynamics. Attractors and repellers are combined into a vector field that governs the blimp’s behaviour. The resulting dynamical systems that generate the flying behaviour is non-linear and presents several attractors and reppelers (typically few) . By design the dynamic systems are tuned so that the behavioural variables are always very close to one attractor. Thus the motion of the airship is controlled by a time series of asymptotically stable states. Computer simulations that integrate the dynamic control architecture and the blimp’s physical model indicate that if parameter values are chosen within reasonable ranges, then the over all system works quite well even in cluttered environments. The stability properties of the dynamic control architecture enable the floating robot to remain robust against perturbations
