Editorial

The papers of this special issue naturally group themselves around a few techniques in autonomous control: various feedback analysis and control solutions under given communication topologies within a group of vehicles appear in five papers (Ren, Chen, Ghabcheloo, de Sousa). Three papers (Salazar-Cruzet, Loebis, Lincoln) deal with the problems of navigation and control of an autonomous four-rotor aircraft, an underwater vehicle and an autonomous cluster of satellites in formation. An innovative idea of autonomous control is presented (Tsankova) using immune network control for stigmergy-based foraging behaviour that is motivated by known behaviours of biological immune systems. A paper (Aslund) proposes a solution to the practically important problem of extending fault tree analysis to algorithmic performance of autonomous systems.

Ren's paper on distributed attitude alignment in spacecraft formation flying deals with a distributed attitude alignment problem for a team of deep space formation flying spacecraft through local information exchange. The author considers three cases of special interest. In the first case, multiple spacecraft converge to their desired attitudes while maintaining relative attitudes during formation manoeuvres under an undirected communication graph. In the second case, multiple spacecraft converge to the same rotation rate while aligning their attitudes under an undirected communication graph. The third case deals with attitude alignment assuming a directed information exchange graph.

A paper on co-operative control of multiple vehicles with limited sensing by Chen et al. develops a navigation function-based co-operative control strategy for multiple unmanned aerial vehicles (UAVs) in the presence of known stationary obstacles and unknown enemy assets.

A paper by Ghabcheloo et al. on nonlinear co-ordinated path following control of multiple wheeled robots with bidirectional communications constraints presents a solution to the problem of steering a group of wheeled robots along given spatial paths while holding a desired inter-vehicle formation pattern. Their solutions take into account the dynamics of the cooperating robots and the constraints imposed by the topology of inter vehicle communications.

A paper on verified hierarchical control architectures for co-ordinated multi-vehicle operations by de Sousa et al. proposes a control architecture for executing multi-vehicle co-ordination algorithms. They present a hierarchical structure that consists of three layers: team controller; vehicle supervisor and manoeuvre controller. They show that the desired team behaviour is achieved by the controller implementation.

The paper by Salazar-Cruzet et al. describes the design of an embedded control system for a four-rotor UAV to perform hover flights. A dynamic model of the vehicle is presented using an Euler–Lagrange approach. An embedded control system architecture is described for autonomous hover flight. The experimental results show that the on-board control system performs satisfactorily.

The paper by Loebis et al. on soft computing techniques in the design of a navigation, guidance and control system for an autonomous underwater vehicle discusses the navigation, guidance and control of an underwater vehicle. The navigation system is based on the global positioning system (GPS) and several inertial navigation system (INS) sensors.

A paper by Lincoln on vision-assisted constrained control of autonomous satellite formation flying examines a solution to autonomous formation flying of satellites where combined inaccuracy problems of position, velocity and attitude estimation, data fusion across the cluster, constraints of actuators, planning of fuel efficient manoeuvres and their robust execution are all considered.

The paper by Tsankova and her colleagues on immune network control for stigmergy-based foraging behaviour of autonomous mobile robots presents a series of experiments in a simulated environment where two autonomous mobile robots gather randomly distributed objects and cluster them on a pile. The co-ordination of the robots' movements is achieved through stigmergy that is an indirect form of communication through the environment. Åslund et al. present a paper on safety analysis of autonomous systems by extended fault tree analysis. Safety is of major concern in many autonomous functions in automotive systems and aerospace. In these application areas it is standard to use fault trees, and a natural question is how to include the performance of these algorithms in a fault tree analysis for safety.

Clearly, some of these papers extend the conceptual horizons of conventional adaptive feedback and robust control schemes. The area of vehicle autonomy in general, dynamical autonomy in particular, raise not only new types of questions but its solutions do not easily fit into classical paradigms of feedback control either. This special issue insisted on rigorous analytical approaches and therefore the analytic methods presented highlight that the paradigms of feedback control systems are being widened to include communications constraints, co-operative strategies, operational verification, safety analysis, etc. These papers also illustrate that, from a control engineering viewpoint, simply classifying these autonomous systems as embedded or hybrid systems may not give justice to the rich architectural and operational details that sophisticated autonomous systems possess.

I hope the reader will share my view that this special issue provides an interesting and valuable cross-section of the many approaches and methods that coexist in the area of autonomous control.