The aim of this paper is to address left invertibility for dynamical systems with inputs and outputs in discrete sets. We study systems that evolve in discrete time within a continuous state-space. Quantized outputs are generated by the system according to a given partition of the state-space, while inputs are arbitrary sequences of symbols in a finite alphabet, which are associated to specific actions on the system. We restrict to the case of contractive dynamics for fixed inputs. The problem of left invertibility, i.e. recovering an unknown input sequence from the knowledge of the corresponding output string, is addressed using the theory of Iterated Function Systems (IFS), a tool developed for the study of fractals. We show how the IFS naturally associated to a system and the geometric properties of its attractor are linked to the left invertibility property of the system. Our main results are a necessary and sufficient condition for a given system to be left invertible with probability one on the space of inputs (i.e. for almost all input sequences), and necessary and sufficient conditions for left invertibility and uniform left invertibility under some weak additional hypotheses. A few examples are presented to illustrate the application of the proposed method.
This paper addresses a security problem in robotic multi-agent systems, where agents are supposed to cooperate according to a shared protocol. A distributed Intrusion Detection System (IDS) is proposed here, that detects possible non- cooperative agents. Previous work by the authors showed how single monitors embedded on-board the agents can detect non- cooperative behavior, using only locally available information. In this paper, we allow such monitors to share the collected information in order to overcome their sensing limitation. In this perspective, we show how an agreement on the type of behavior of a target-robot may be reached by the monitors, through execution of a suitable consensus algorithm. After formulating a consensus problem over non-scalar quantities, and with a generic update function, we provide conditions for the consensus convergence and an upper bound to its transient duration. Effectiveness of the proposed solution is finally shown through simulation of a case study.
In this paper, we address the optimal connected sensing coverage problem, i.e., how mobile sensors with limited sensing capabilities can cooperatively adjust their locations so as to maximize the extension of the covered area while avoiding any internal "holes", areas that are not covered by any sensor. Our solution consists in a distributed motion algorithm that is based on an original extension of the Voronoi tessellation.
In this paper we consider the problem of designing controllers for linear plants to be implemented in embedded platforms under stringent real-time constraints. These include preemptive scheduling schemes, under which the maximum execution time allowed for control software tasks is uncertain. We propose an ``anytime control'' design approach, consisting in a hierarchy of controllers for the same plant. Higher controllers in the hierarchy provide better closed-loop performance, while typically requiring a larger worst-case execution time. We provide a procedure for the design of controllers which, together with a conditioning process of the stochastic scheduling, provides better performance than prevailing worst case-based design, while guaranteeing almost sure stability of the resulting switching system.
In this paper we consider closed loop stability of a number of different software tasks implementing a hierarchy of real-time controllers for a given plant, i.e.
In this paper we present a robust adaptive controller based on a neural network (NN) for a variable stiffness actuator (VSA). The controller is able to independently set the mechanical stiffness and position at the joint shaft to guarantee robustness with respect to slowly time-varying and unmodeled friction coefficients affecting the dynamics of the actuator. The lumped uncertainties of the VSA including unmodeled dynamics are considered and approximated by a simple NN so that the controlled system is asymptotically stable, and remains effective while process conditions vary. To cope with the reconstruction error of the NN, a sliding mode like additional robust control term is introduced. The proofs for the uniformly ultimately bounded (UUB) and uniform asymptotic (UAS) stabilities for the closed-loop system are provided in detail via Lyapunov theory. Simulation and experimental results are reported in support of both validity and performance of the proposed approach.
The paper considers the problem of driving a formation of autonomous mobile agents. The group of mobile devices is described as a leader–follower network, where the followers update their position using a simple local consensus procedure, while the leaders, whose positions represent the control inputs of the network, are free to move. We characterize the transient behavior of the network, and solve the containment problem without relying on auxiliary sensors.
This paper presents a correct solution to the optimal feedback control for a nonholonomic vehicle with limited field-of-view. Previous work on this subject has shown that the search for a shortest path can be limited to simple families of trajectories. We preliminarily provide an extension of the alphabet of optimal control words, to cover some regions of the vehicle plane where the synthesis of turns out to be suboptimal. The main contribution of this paper is an algorithm to translate the optimal synthesis to the image plane, thus enabling a purely image-based optimal control scheme. This allows better performance and increases the robustness of the overall process, avoiding the need of slowly-converging and error-prone parameter estimation algorithms. Simulations and experiments are reported which demonstrate the effectiveness of the proposed technique.
This paper presents design and performance of a novel joint based actuator for a robot run by variable stiffness actuation, meant for systems physically interacting with humans. This new actuator prototype (VSA-II) is developed as an improvement over our previously developed one reported in [9], where an optimal mechanical-control co-design principle established in [7] is followed as well. While the first version was built in a way to demonstrate effectiveness of variable impedance actuation (VIA), it had limitations in torque capacities, life cycle and implementability in a real robot. VSA-II overcomes the problem of implementability with higher capacities and robustness in design for longer life. The paper discusses design and stiffness behaviour of VSA-II in theory and experiments. A comparison of stiffness characteristics between the two actuator is discussed, highlighting the advantages of the new design. A simple, but effective PD scheme is employed to independently control joint-stiffness and joint-position of a 1-link arm. Finally, results from performed impact tests of 1- link arm are reported, showing the effectiveness of stiffness variation in controlling value of a safety metric.
In the RUNES project a disaster relief tunnel scenario is being developed in which mobile robots are used to restore the radio network connectivity in a stationary sensor network. A component-based software development approach has been adopted. Two components are described in this paper. A localization component that uses ultrasound and dead reckoning to decide the robot positions and a collision avoidance component that ensures that the robots do not collide with each other.
In this paper a novel higher order method for the resolution of non linear equations is proposed. The particular application to the mobile robot navigation in an environment with obstacles is considered. The proposed method is based on the {\em embedded-relaxed} approach in which the dimension of the resolution space is augmented and a different and faster direction toward the root is computed. The method is proved to converge with higher order for the augmented resolution space of dimension 2 and 3. Finally, the method is applied to the problem of mobile robot navigation between obstacles considered as repulsive potentials.
