Adaptive Leader-Follower Formation in Cluttered Environment Using Dynamic Target Reconfiguration

Abstract

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.

A novel safe and flexible control strategy based on target reaching for the navigation of urban vehicles

“…Section 5.1.1) will validate the above approach. Moreover, (30) and (35) show the relations between initial configuration, controller parameters and error of reaching the target. Therefore, for certain initial configuration and defined error bounds, the controller parameters can be obtained.…”

“…Indeed, for a specific parameter value K, if the controller can reach the target (with e θ less than E angle for a time t f given according to (30)), then for the same K parameters, e θ must be less than E angle for a time t > t f .…”

“…From (30), the orientation error e θ depends on the initial orientation error e θo and the controller parameters (K d , K x , K o , K θ ).…”

“…The desired final configuration is (x T , y T , θ T ) ≡ (15, 4, 0°) and v T = 1 m/s. The controller parameters K are designed considering E dist ≤ 0.1 m and E angle ≤ 5°using (30) and (35). Hence, it is designed such that K = (1/d i , 0.6, 10, 0.1, 0.3, 0.01), d i = 10.6 m is the minimum initial euclidean distance to the target.…”

Graph-based distributed control for adaptive multi-robot patrolling through local formation transformation

“…While the attractor dynamic approach limits authority over the formation topology to situations in which no obstacles are present, it nevertheless breaks the formation during obstacle circumvention. Dynamic change of formation has been explored in [3]. Designed for unmanned ground vehicles, this method performs well in open outdoor spaces, but may not be adequately reactive indoors.…”