On the Robust Synthesis of Logical Consensus Algorithms for Distributed Intrusion Detection

We introduce a novel consensus mechanism by which the agents of a network can reach an agreement on the value of a shared logical vector function depending on binary input events. Based on results on the convergence of finite-state iteration systems, we provide a technique to design logical consensus systems that minimizing the number of messages to be exchanged and the number of steps before consensus is reached, and tolerating a bounded number of failed or malicious agents. We provide sufficient joint conditions on the input visibility and the communication topology for the method’s applicability. We describe the application of our method to two distributed network intrusion detection problems

3 known landmarks are enough for solving planar bearing SLAM and fully reconstruct unknown inputs

In this paper we show that for an observer moving in the plane with no other information than the measurement of relative bearing to three known landmarks, it is possible to completely reconstruct its position and velocity. In particular this applies to the case where no model of the vehicle, nor odometry or acceleration measurements are available. Furthermore, in the same hypotheses, the position of any further landmark can be reconstructed from its bearing only. These results are more general than what is currently known on nonlinear observability of the SLAM problem, which relies on known observer velocities. Our results are also more general than the 2D version of known structure-from-motion observability results, which assume unknown but constant velocities. The proposed method is used to build a nonlinear observer directly applicable to a range of problems from computer vision to autonomous visual navigation

On the role of robot configuration in Cartesian stiffness control

The stiffness ellipsoid, i.e. the locus of task-space forces obtained corresponding to a deformation of unit norm in different directions, has been extensively used as a powerful representation of robot interaction capabilities. The size and shape of the stiffness ellipsoid at a given end-effector posture are influenced by both joint control parameters and - for redundant manipulators - by the chosen redundancy resolution configuration. As is well known, impedance control techniques ideally provide control parameters which realize any desired shape of the Cartesian stiffness ellipsoid at the end-effector in an arbitrary non-singular configuration, so that arm geometry selection could appear secondary. This definitely contrasts with observations on how humans control their arm stiffness, who in fact appear to predominantly use arm configurations to shape the stiffness ellipsoid. To understand this discrepancy, we provide a more complete analysis of the task-space force/deformation behavior of redundant arms, which explains why arm geometry also plays a fundamental role in interaction capabilities of a torque controlled robot. We show that stiffness control of realistic robot models with bounds on joint torques can't indeed achieve arbitrary stiffness ellipsoids at any given arm configuration. We first introduce the notion of maximum allowable Cartesian force/displacement (“stiffness feasibility”) regions for a compliant robot. We show that different robot configurations modify such regions, and explore the role of different configurations in defining the performance limits of Cartesian stiffness controllers. On these bases, we design a stiffness control method that suitably exploits both joint control parameters and redundancy resolution to achieve desired task-space interaction behavior

Convergence Analysis of Distributed Set-Valued Information Systems

This paper focuses on the convergence of information in distributed systems of agents communicating over a network. The information on which the convergence is sought is not rep- resented by real numbers, as often in the literature, rather by sets. The dynamics of the evolution of information across the net- work is accordingly described by set-valued iterative maps. While the study of convergence of set-valued iterative maps is highly complex in general, this paper focuses on Boolean maps, which are comprised of arbitrary combinations of unions, intersections, and complements of sets. For these important class of systems, we provide tools to study both global and local convergence. A distributed geographic information system, leading to successful information reconstruction from partial and corrupted data, is used to illustrate the applications of the proposed methods

A Self-Routing Protocol for Distributed Consensus on Logical Information

In this paper, we address decision making problems, depending on a set of input events, with networks of dynamic agents that have partial visibility of such events. Previous work by the authors proposed so-called logical consensus approach, by which a network of agents, that can exchange binary values representing their local estimates of the events, is able to reach a unique and consistent decision. The approach therein proposed is based on the construction of an iterative map, whose computation is centralized and guaranteed under suitable conditions on the input visibility and graph connectivity. Under the same conditions, we extend the approach in this work by allowing the construction of a logical linear consensus system that is globally stable in a fully distributed way. The effectiveness of the proposed method is showed through the real implementation of a wireless sensor network as a framework for the surveillance of an urban area

Human-Like Impedance and Minimum Effort Control for Natural and Efficient Manipulation

Humans incorporate and switch between learnt neuromotor strategies while performing complex tasks. Towards this purpose, kinematic redundancy is exploited in order to achieve optimized performance. Inspired by the superior motor skills of humans, in this paper, we investigate a combined free motion and interaction controller in a certain class of robotic manipulation. In this bimodal controller, kinematic degrees of redundancy are adapted according to task-suitable dynamic costs. The proposed algorithm attributes high priority to minimum-effort controller while performing point to point free space movements. Once the robot comes in contact with the environment, the Tele-Impedance, common mode and configuration dependent stiffness (CMS-CDS) controller will replicate the human’s estimated endpoint stiffness and measured equilibrium position profiles in the slave robotic arm, in real-time. Results of the proposed controller in contact with the environment are compared with the ones derived from Tele-Impedance implemented using torque based classical Cartesian stiffness control. The minimum-effort and interaction performance achieved highlights the possibility of adopting human-like and sophisticated strategies in humanoid robots or the ones with adequate degrees of redundancy, in order to accomplish tasks in a certain class of robotic manipulatio

A Spherical Active Joint for Humanoids and Humans

Both humanoid robotics and prosthetics rely on the possibility of implementing spherical active joints to build dexterous robots and useful prostheses. There are three possible kinematic implementations of spherical joints: serial, parallel, and hybrid, each one with its own advantages and disadvantages. In this letter, we propose a hybrid active spherical joint, that combines the advantages of parallel and serial kinematics, to try and replicate some of the features of biological articulations: large workspace, compact size, dynamical behavior, and an overall spherical shape. We compare the workspace of the proposed joint to that of human joints, showing the possibility of an almost-complete coverage by the device workspace, which is limited only by kinematic singularities. A first prototype is developed and preliminarly tested as part of a robotic shoulder joint

The Change in Fingertip Contact Area as a Novel Proprioceptive Cue

Humans, many animals, and certain robotic hands have deformable fingertip pads [1, 2]. Deformable pads have the advantage of conforming to the objects that are being touched, ensuring a stable grasp for a large range of forces and shapes. Pad deformations change with finger displacements during touch. Pushing a finger against an external surface typically provokes an increase of the gross contact area [3], potentially providing a relative motion cue, a situation comparable to looming in vision [4]. The rate of increase of the area of contact also depends on the compliance of the object [5]. Because objects normally do not suddenly change compliance, participants may interpret an artificially induced variation in compliance, which coincides with a change in the gross contact area, as a change in finger displacement, and consequently they may misestimate their finger’s position relative to the touched object. To test this, we asked participants to compare the perceived displacements of their finger while contacting an object varying pseudo-randomly in compliance from trial to trial. Results indicate a bias in the perception of finger displacement induced by the change in compliance, hence in contact area, indicating that participants interpreted the altered cutaneous input as a cue to proprioception. This situation highlights the capacity of the brain to take advantage of knowledge of the mechanical properties of the body and of the external environment