Pose consensus based on dual quaternion algebra with application to decentralized formation control of mobile manipulators

This paper presents a solution based on dual quaternion algebra to the general problem of pose (i.e., position and orientation) consensus for systems composed of multiple rigid-bodies. The dual quaternion algebra is used to model the agents' poses and also in the distributed control laws, making the proposed technique easily applicable to time-varying formation control of general robotic systems. The proposed pose consensus protocol has guaranteed convergence when the interaction among the agents is represented by directed graphs with directed spanning trees, which is a more general result when compared to the literature on formation control. In order to illustrate the proposed pose consensus protocol and its extension to the problem of formation control, we present a numerical simulation with a large number of free-flying agents and also an application of cooperative manipulation by using real mobile manipulators

Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey

summary:Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research

Consensus Tracking and Containment in Multiagent Networks With State Constraints

The ability of tracking is an important prerequisite for multiagent networks to perform collective activities. This article investigates the problem of containment for a weighted multiagent network with continuous-time agents under state constraints. The network is composed of uninformed and informed agents, where the latter receive external inputs. A new general class of distributed nonlinear controllers is designed for accomplishing both containment and consensus tracking, where the state of each agent is required to stay in its desired convex constraint set. We show that, by using matrix analysis, convex analysis, and Lyapunov theory, all agents eventually converge to the convex hull formed by the external inputs while they obey their constraints during the transience. No relationship is assumed between the convex hull and the intersection of all constraint sets. The consensus tracking problem with a single external input is also solved under this framework. As a generalization, we tackle the multiscaled constrained containment problem, where agents can specify their desired buffer zones by either zooming in or zooming out the convex hull. Numerical examples are provided to illustrate the theoretical results

Fast Convergence in Consensus Control of Leader-Follower Multi-Agent Systems

In this thesis, different distributed consensus control strategies are introduced for a multi-agent network with a leader-follower structure. The proposed strategies are based on the nearest neighbor rule, and are shown to reach consensus faster than conventional methods. Matrix equations are given to obtain equilibrium state of the network based on which the average-based control input is defined accordingly. Two network control rules are subsequently developed, where in one of them the control input is only applied to the leader, and in the other one it is applied to the leader and its neighbors. The results are then extended to the case of a time-varying network with switching topology and a relatively large number of agents. The convergence performance under the proposed strategies in the case of a time-invariant network with fixed topology is evaluated based on the location of the dominant eigenvalue of the closed-loop system. For the case of a time-varying network with switching topology, on the other hand, the state transition matrix of the system is investigated to analyze the stability of the proposed strategies. Finally, the input saturation in agents' dynamics is considered and the stability of the network under the proposed methods in the presence of saturation is studied

Dynamic Resilient Containment Control in Multirobot Systems

In this article, we study the dynamic resilient containment control problem for continuous-time multirobot systems (MRSs), i.e., the problem of designing a local interaction protocol that drives a set of robots, namely the followers, toward a region delimited by the positions of another set of robots, namely the leaders, under the presence of adversarial robots in the network. In our setting, all robots are anonymous, i.e., they do not recognize the identity or class of other robots. We consider as adversarial all those robots that intentionally or accidentally try to disrupt the objective of the MRS, e.g., robots that are being hijacked by a cyber–physical attack or have experienced a fault. Under specific topological conditions defined by the notion of (r,s)-robustness, our control strategy is proven to be successful in driving the followers toward the target region, namely a hypercube, in finite time. It is also proven that the followers cannot escape the moving containment area despite the persistent influence of anonymous adversarial robots. Numerical results with a team of 44 robots are provided to corroborate the theoretical findings