In this paper, a distributed controller–observer schema for tracking control of the centroid and of the relative formation of a multi-robot system with first-order dynamics is presented. Each robot of the team uses a distributed observer to estimate the overall system state and a motion control strategy for tracking control of time-varying centroid and formation. Proof of the overall convergence of the controller–observer schema for different kinds of connection topologies, as well as for the cases of unsaturated and saturated control inputs is presented. In particular, the solution is proven to work in the case of strongly connected non-switching topologies and in the case of balanced strongly connected switching topologies. In order to complete the work, the approach is validated by experimental tests with a team of five wheeled mobile robots.

In this paper, the experimental validation of a behavior-based technique for multirobot systems (MRSs), namely, the Null-Space-based Behavioral (NSB) control, is presented. The NSB strategy, inherited from the singularity-robust task-priority inverse kinematics for industrial manipulators, has been recently proposed for the execution of different formation-control missions with MRSs. In this paper, focusing on the experimental details, the validation of the approach is achieved by performing different experimental missions, in presence of static and dynamic obstacles, with a team of grounded mobile robots available at the Laboratorio di Automazione Industriale of the Universita degli Studi di Cassino.

This paper presents an adaptive trajectory tracking control strategy for quadrotor micro aerial vehicles (MAVs). The proposed approach, while maintaining the common assumption of an orientation dynamics faster than the translational one, removes the assumption of absence of external disturbances and of geometric center coincident with the Center of Mass (CoM). In particular, the trajectory tracking control law is made adaptive with respect to the presence of external forces and moments (e.g., due to wind) and to the uncertainty of parameters of the dynamic model, such as the position of the CoM. A stability analysis is presented to analytically support the proposed controller, while numerical simulations are provided in order to validate its performance.

In this paper, we present a distributed fault detection and isolation (FDI) strategy for a team of networked robots that builds on a distributed controller-observer schema. Remarkably different from other works in literature, the proposed FDI approach makes each robot of the team able to detect and isolate faults occurring on other robots, even if they are not direct neighbors. By means of a local observer, each robot can estimate the overall state of the team and it can use such an estimate to compute its local control input to achieve global tasks. The same information used by the local observers is also used to compute residual vectors, whose aim is to allow the detection and the isolation of actuator faults occurring on any robot of the team. Adaptive thresholds are derived based on the dynamics of the residual vectors by considering the presence of nonzero initial observer estimation errors, and noise terms affecting state measurement and model dynamics. The approach is validated via both numerical simulations and experiments involving four Khepera III mobile robots.

In this paper the application of a behavior-based control approach, namely the null-space-based behavioral control, to coordinate a fleet of autonomous surface vessels is presented. The NSB can be considered as a centralized guidance system aimed at driving the fleet in complex environments while simultaneously performing multiple tasks, i.e., obstacle avoidance or keeping a formation. In order to apply the guidance system to a fleet of underactuated surface vessels, the NSB works in combination with a low-level maneuvering control that, taking care of the dynamics of the vessels, elaborates the motion commands to generate the generalized forces at the actuators. The guidance system has been simulated in the accomplishment of a mission in presence of obstacles and sea current in the environment