New York City College of Technology

Robotics & Intelligent Systems Laboratory




•   Distributed Coordination of Robotic Swarms

      Leading Faculty: Dr. Li


Fig.1.  A swarm of 20 mobile robots avoid an obtacle while keeping the formation.

The natural phenomena of swarms, characterized by grouping of a large number of entities, can be observed in many living beings such as flocks of birds and schools of fish. The inspiring aspect of these phenomena is that although the intelligence of the individual members of the swarm is limited, a sophisticated and efficient group behavior is still achieved. In the last few years, distributed coordination control of a large scale multi-agent dynamical system (e.g., robotic swarms) has invoked increasing interest in control and robotics community. A large group of mobile agents (e.g., mobile robots or mobile sensors), geared with computing, sensing and communication devices can serve as a platform for a variety of coordination tasks in civilian and military applications.

In this project, we study the underlying mechanisms in natural swarms, develop a biologically inspired systematic methodology to analyze the behavior of a large group of mobile agents, and develop a unified framework for the controller design of a general range of coordinated motions of robotic swarms.  We use algebraic graphs to model the topologies of the swarm that embody the neighborhood, communication or the sensing relations among the members. We consider the general situation that the swarm’s topology dynamically changes as the spacing among agents evolves with time. By exploiting the developed framework, we investigate and design scalable controllers for several specific application scenarios of the coordinated motion of the swarm, namely, mobilization, rendezvous and virtual leader tracking control.


•  Dynamic Spectrum Coordination in Cognitive Mesh Networks

    Leading Faculty:  Dr. Li


Fig.2. 15 nodes with a Primary User (Node 7). The chanel being used by each node is indicated by different colors.

Fig.3 The 14 nodes converge to a common channel.
Cognitive Radios (CR) have been advanced as a technology for an opportunistic use of under-utilized radio spectrum. Cognitive mesh network is an emerging wireless mesh network that exploits CR technology to achieve reliable communication. A distributed spectrum coordination algorithm needs to be designed to make the nodes in cognitive mesh network approach to a common spectrum for establishing communication links among them. A cognitive mesh network with dynamic spectrum coordination will be greatly beneficial to a wide range of applications. For example, in a hostile battlefield, many communication channels may be interfered or jammed, which disables the communications of many nodes. A cognitive mesh network can adaptively and rapidly shift the common channel to another available channel and provide highly reliable communication.

In this project, we aim to deliver both theoretical foundation and practical solution to dynamic spectrum coordination in cognitive mesh networks. First, we will propose a biologically inspired, scalable, and mathematically provable distributed spectrum coordination algorithm. Then, we will for the first time provide a general analytical study of the spectrum selection behaviors of individual nodes and the entire network. We will also analytically investigate the fundamental features of the convergence time of the proposed algorithm. Besides the theoretical work, we will implement the developed algorithm on a small scale CR mesh network. 



•   Miniature Quadrocopters: A  Reconfigureable Intelligent Platform for 3D Urban Environment Exploration 

     Leading Faculty:  Dr. Li and Dr. Wang

Fig.4 Our customized autopilot board  

A variety of civilian and security applications in urban areas cluttered with skyscrapers, such as crowd control, security surveillance, emergence response and disaster rescue, require a comprehensive and complete scene exploration and understanding of the environments. Traditional helicopters and ground vehicles may not be accessible to certain constrained or hostile scenes and cannot provide prompt first-hand information.

In this project, we aim to design and develop a team of compact unmanned quadrocopters that can be deployed 24/7 and accessible to constrained environments for mapping and scene understanding. We will explore the aerodynamic advantage of quadrorotors and use nontraditional motor to achieve a reliable and long mission operation by limited power source. The unique quadrorotor design will eliminate the the main chassis rotor and antitorque rotor, which will lead to a better aerodynamic maneuverability, and a high reliability in the case of rotor failure. We design and cutomize a motor driver and an autopilot system to stably control the motor's flight, which will receive control and trajectory command from upper-level system that will include advanced sensing, decision-making and computing components.  


•   Wearable Vision System for Scene Understanding

     Leading Faculty: Dr. Li, Dr. Wang and Dr. Kwon

With the advancement of miniature sensing and computing devices, vision systems can be made smaller and smaller. In this project, we aim to design and develop a compact and portable vision system for hand gesture recogniztion and scene understanding. This system can be used to help visually or phonetically challenged people become more adaptable to their surrounding environments.


 •   Heteromorphism Robotics

        Leading Faculty:  Dr. Li

In this project we aim to design and develop a heteromorphism robot that can reform its structure and reconfigure its network for an agile adjustment corresponding to the locomotion environment and terrains.


Last Update: Oct. 1, 2017

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