This paper deals with reactive and flexible humanlike autonomous vehicle navigation. A human driver reactively guides his vehicle, performing a smooth trajectory within the roads limits until reaching the defined goal. To obtain a similar behavior with an unmanned ground vehicle (UGV), this paper proposes a flexible control law to drive a vehicle towards desired static or dynamic targets based on a novel definition of control variables and Lyapunov stability analysis. Moreover, a target assignment strategy, combined with an appropriate sigmoid function, that allow to perform smooth, flexible and safe vehicle navigation through successive waypoints is presented. The stability of the proposed control strategy is proved according to Lyapunov synthesis. Simulations and experiments are performed in different cases to demonstrate the reliability and efficiency of the control strategy.

This paper presents a control architecture for safe and smooth navigation of a group of Unmanned Ground Vehicles (UGV) while keeping a specific formation. The formation control is based on Leader-follower and Behavioral approaches. The proposed control architecture is designed to allow the use of a single control law for different multi-vehicle contexts (navigation in formation, transition between different formation shapes, obstacle avoidance, etc.). The obstacle avoidance strategy is based on the limit-cycle approach while taking into account the dimension of the formation. A new Strategy for Formation Reconfiguration (SFR) of the group of UGVs based on suitable smooth switching of the set-points (according, for instance, to the encountered obstacles or the new task to achieve) is proposed. The inter-vehicles collisions are avoided during the SFR using a penalty function acting on the vehicle velocities. Different simulations on cluttered environments show the performance and the efficiency of the proposal, to obtain fully reactive and distributed control strategy for the navigation in formation of a group of UGVs.

This paper deals with the problem of mobile robot navigation in cluttered environment. An adaptive elliptic trajectories are exploited for reactive obstacle avoidance using only position information and uncertain range data. The used obstacle avoidance strategy is based on elliptic limit-cycle principle where each obstacle is surrounded by an ellipse. The ellipse parameters are computed on-line using the sequence of uncertain range data. An online heuristic method combined with the Extended Kalman Filter (EKF) is used to compute the ellipse parameters. It is demonstrated that this process insures that all range data are surrounded by the computed ellipse. Moreover, this paper proposes a single control law to the multi-controller architecture where is embedded the reactive obstacle avoidance algorithm. This proposed control law is based on Kanayama control law and it is designed to improve the performance of the controllers. The stability of this control architecture is proved according to Lyapunov synthesis. Simulations and experiments in different environments were performed to demonstrate the efficiency and the reliability of the proposed on-line navigation in cluttered environment.

h i g h l i g h t s• Novel control strategy based on static/dynamic target reaching for autonomous navigation.• Control law is synthesized using a Lyapunov function based on a new set of variables.• Interesting properties of the control law in terms of stability and flexibility. • Sequential target assignment strategy allows performing safe navigation. • Experiments using actual vehicles and several simulations show the advantages of the proposal. a b s t r a c tThis paper presents a complete framework for reactive and flexible autonomous vehicle navigation. A human driver reactively guides a vehicle to the final destination while performing a smooth trajectory and respecting the road boundaries. The objective of this paper is to achieve similar behavior in an unmanned ground vehicle to reach a static or dynamic target location. This is achieved by using a flexible control law based on a novel definition of control variables and Lyapunov synthesis. Furthermore, a target assignment strategy to enable vehicle navigation through successive waypoints in the environment is presented. An elementary waypoint selection method is also presented to perform safe and smooth trajectories. The asymptotic stability of the proposed control strategy is proved. In addition, an accurate estimation of the maximum error boundary, according to the controller parameters, is given. With this indicator, the vehicle navigation will be safe within a certain boundaries. Simulations and experiments are performed in different cases to demonstrate the flexibility, reliability and efficiency of the control strategy. Our proposal is compared with different navigation methods from the literature such as those based on trajectory following.