Zhen Kan

Network Connectivity Preserving Formation Stabilization and Obstacle Avoidance via a Decentralized Controller

A decentralized control method is developed to enable a group of agents to achieve a desired global configuration while maintaining global network connectivity and avoiding obstacles, using only local feedback and no radio communication between the agents for navigation. By modeling the interaction among the agents as a graph, and given a connected initial graph with a desired neighborhood between agents, the developed method ensures the desired communication links remain connected for all time. To guide the agents to a desired configuration while avoiding obstacles, a decentralized controller is developed based on the navigation function formalism. By proving that the proposed controller is a qualified navigation function, convergence to the desired formation is guaranteed.

Saturated RISE Feedback Control for a Class of Second-Order Nonlinear Systems

A saturated controller is developed for a class of uncertain, second-order, nonlinear systems which includes time-varying and nonlinearly parameterized functions with bounded disturbances using a continuous control law with smooth saturation functions. Based on the robust integral of the sign of the error (RISE) control methodology, the developed controller is able to utilize the benefits of high gain control strategies while guaranteeing saturation limits are not surpassed. The bounds on the control are known a priori and can be adjusted by changing the feedback gains. The saturated controller yields asymptotic tracking despite model uncertainty and added disturbances in the dynamics. Experimental results using a two-link robot manipulator demonstrate the performance of the developed controller.

Ensuring network connectivity during formation control using a decentralized navigation function

In many applications of formation control, agents coordinate and communicate to make appropriate decisions. Connectivity of the network is paramount in such applications. The goal in this paper is to drive a group of agents with limited sensing capabilities to a desired configuration while ensuring the connectivity of the wireless communication network among the agents. Based on a navigation function formalism, a decentralized cooperative controller is proposed where agent only uses information within its sensing zone to guarantee connectivity maintenance of the network and achieve the desired formation with collision avoidance between themselves and with obstacles in the environment.

Structure and motion estimation of a moving object using a moving camera

A solution is presented to the problem of estimating the structure and motion of a moving object seen from a moving camera. A nonlinear observer is proposed, which asymptotically identifies the structure and motion of the moving object, when the camera motion is persistently exciting. The object is assumed to be moving with constant velocities. The proposed method makes no assumptions on the minimum number of views or point correspondences as required by the existing approaches.

Graph Matching-Based Formation Reconfiguration of Networked Agents With Connectivity Maintenance

Various applications require networked agents to cooperatively achieve specified formations. In this paper, formation reconfiguration for a group of identical agents with limited communication capabilities is considered. Since the considered agents are identical, their roles are interchangeable, and each position in the desired formation can be taken by any agent. To reduce the total amount of node movement required for formation reconfiguration, a weighted graph-matching-based node-mapping strategy is developed to specify the node correspondence between an arbitrary initial graph and the desired graph. After the node mapping is determined, agents are required to move physically to form the desired formation. Since agents are only able to communicate within a certain range, formation reconfiguration must be accomplished with network connectivity constraints (i.e., specified nodes remain within specified sensing and communication ranges). A decentralized control scheme is developed to guarantee network connectivity by maintaining a desired neighborhood determined by the node-mapping algorithm, and to ensure convergence of all agents to the desired configuration with collision avoidance among agents. The developed strategy is demonstrated through simulation results.

Asymptotic Synchronization of a Leader-Follower Network of Uncertain Euler-Lagrange Systems

This paper investigates the synchronization of a network of Euler-Lagrange systems with leader tracking. The Euler-Lagrange systems are heterogeneous and uncertain and contain bounded, exogenous disturbances. Network communication is governed by an undirected topology. The network leader has a time-varying trajectory which is known to only a subset of the follower agents. A Robust Integral Sign of the Error (RISE) based decentralized control law is developed to guarantee semi-global asymptotic agent synchronization and leader tracking.

Structure estimation of a moving object using a moving camera: An unknown input observer approach

A state observer is designed for estimating the structure of a moving object with time-varying velocities seen by a moving camera. A nonlinear unknown input observer strategy is used where the objects velocity is considered as an unknown input to the perspective dynamical system. The object is assumed to be moving on a ground plane. The downward-looking camera observing the moving object is also moving (e.g., attached to an air vehicle) with known velocities. The developed method provides the first causal, observer-based structure estimation algorithm for a moving camera viewing a moving object with unknown time-varying object velocities.

Containment control for a social network with state-dependent connectivity

Social interactions influence our thoughts, opinions and actions. In this paper, social interactions are studied within a group of individuals composed of influential social leaders and followers. Each person is assumed to maintain a social state, which can be an emotional state or an opinion. Followers update their social states based on the states of local neighbors, while social leaders maintain a constant desired state. Social interactions are modeled as a general directed graph where each directed edge represents an influence from one person to another. Motivated by the non-local property of fractional-order systems, the social response of individuals in the network are modeled by fractional-order dynamics whose states depend on influences from local neighbors and past experiences. A decentralized influence method is then developed to maintain existing social influence between individuals (i.e., without isolating peers in the group) and to influence the social group to a common desired state (i.e., within a convex hull spanned by social leaders). Mittag-Leffler stability methods are used to prove the asymptotic convergence of the networked fractional-order system.

On the robustness of large 1-D network of double integrator agents

We study the robustness to external disturbances of large 1-D network of double-integrator agents with distributed control. We provide precise quantitative comparison of certain H∞ norm between two common control architectures: predecessor-following and symmetric bidirectional. In particular, we show that the scaling laws of the H∞ norm for predecessor-following architecture is O(αN) (α >; 1), but only O(N3) for symmetric bidirectional architecture, where N is the number of agents in the network. The results for symmetric bidirectional architecture are obtained by using a PDE model to approximate the closed-loop dynamics of the network for large N. Numerical calculations show that the PDE approximation provides accurate predictions even when N is small. In addition, we examine the robustness of asymmetric bidirectional architecture. Numerical simulations show that with judicious asymmetry in the velocity feedback, the robustness of the network can be improved considerably over symmetric bidirectional and predecessor-following architectures.

Ensuring network connectivity for nonholonomic robots during decentralized rendezvous

In a multi-robot system, robots are typically required to collaborate over a communication network to achieve objectives cooperatively. Due to the limited communication and sensing capabilities on each robot, the cooperative objective must be accomplished while ensuring that specified robots stay within each others sensing and communication ranges and that the overall network remains connected. In this paper, a dipolar navigation function and corresponding time-varying continuous controller is developed for repositioning and reorienting a group of wheeled robots with nonholonomic constraints. Only local sensing feedback information from neighbors is used to navigate the robots and maintain network connectivity, which indicates that communication is available when required for various tasks, but communication is not required for navigation. Simulation results demonstrate the performance of the developed approach.