John S. Bay

Bio: John S. Bay is an academic researcher from Virginia Tech. The author has contributed to research in topics: Mobile robot & Control theory. The author has an hindex of 17, co-authored 40 publications receiving 1461 citations. Previous affiliations of John S. Bay include Ohio State University & Raytheon.

Fundamentals of Linear State Space Systems

Abstract: Models of linear systems vectors and vector spaces linear operators on vector spaces eigenvalues and eignevectors functions of vector matrices solutions to state equations system stability controllability and observability system realizations state feedback and observers introduction to optimal control and estimation mathematical tables MATLAB command summaries.

Toward the development of a material transport system using swarms of ant-like robots

Abstract: A decentralized method for controlling a homogeneous swarm of autonomous mobile robots that collectively transport a single palletized load is proposed. The small tank-like robots have no advanced sensory or communications capabilities. They have no information on the position or number of other robots transporting the small pallet. Instead, all information needed by the robots is derived from the dynamics inherent when the system of robots is contacting a common rigid body. Each robot derives the required local information from a force sensor mounted at the point at which it contacts the pallet. A distributed control law is derived, and the resulting stable behavior of the system is verified by computer simulation. >

Modeling of a Neural Pattern Generator with Coupled nonlinear Oscillators

Abstract: A set of van der Pol oscillators is arranged in a network in which each oscillator is coupled to each other oscillator. Through the selection of coupling coefficients, the network is made to appear as a ring and as a chain of coupled oscillators. Each oscillator is provided with amplitude, frequency, and offset parameters which have analytically indeterminable effects on the output waves. These systems are simulated on the digital computer in order to study the amplitude, frequency, offset, and phase relationships of the waves versus parameter changes. Based on the simulations, systems of coupled oscillators are configured so that they exhibit stable patterns of signals which can be used to model the central pattern generator (CPG) of living organisms. Using a simple biped as an example locomotory system, the CPG model generates control signals for simulated walking and jumping maneuvers. It is shown that with parameter adjustments, as guided by the simulations, the model can be made to generate kinematic trajectories which closely resemble those for the human walking gait. Further-more, minor tuning of these parameters along with some algebraic sign changes of coupling coefficients can effect a transition in the trajectories to those of a two-legged hopping gait. The generalized CPG model is shown to be versatile enough that it can also generate various n-legged gaits and spinal undulatory motions, as in the swimming motions of a fish.

Network-Centric Systems for Military Operations in Urban Terrain: The Role of UAVs

Abstract: Military systems are the motivational driver for much of the technology development conducted at applied research laboratories around the world. As the needs of the world's militaries change, so does the focus of this research and development. In this paper, we discuss how the fundamental characteristics of military operations in urban terrain (MOUT) impose requirements and constraints on sensing and reconnaissance. We highlight the importance of a new class of small unmanned aerial vehicles (UAVs) for network-centric military urban operations. We review some of the UAVs that have been developed in recent years, and that are under development, with particular attention to their endurance, portability, performance, payload, and communication capabilities. Selected university testbeds are also briefly noted. Over the last few years there has been considerable research focused on how these small UAVs, both individually and collectively, can operate autonomously in urban environments and help capture and communicate needed information. We discuss some of this research; specific topics covered include guidance and control for autonomous operation, multi-UAV coordination and route optimization, and ad-hoc networking with UAV nodes. A new concept of operations is described that relies on coordination and control of a heterogeneous suite of small UAVs for surveillance and reconnaissance operations in urban terrain

Multiple stochastic learning automata for vehicle path control in an automated highway system

Abstract: This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results.

ALLIANCE: an architecture for fault tolerant multirobot cooperation

Abstract: ALLIANCE is a software architecture that facilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled subtasks that may have ordering dependencies. ALLIANCE allows teams of robots, each of which possesses a variety of high-level functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot's own internal states. ALLIANCE is a fully distributed, behaviour-based architecture that incorporates the use of mathematically-modeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup.

Cooperative mobile robotics: antecedents and directions

Abstract: There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.

Flying Ad-Hoc Networks (FANETs)

Abstract: One of the most important design problems for multi-UAV (Unmanned Air Vehicle) systems is the communication which is crucial for cooperation and collaboration between the UAVs. If all UAVs are directly connected to an infrastructure, such as a ground base or a satellite, the communication between UAVs can be realized through the in-frastructure. However, this infrastructure based communication architecture restricts the capabilities of the multi-UAV systems. Ad-hoc networking between UAVs can solve the problems arising from a fully infrastructure based UAV networks. In this paper, Flying Ad-Hoc Networks (FANETs) are surveyed which is an ad hoc network connecting the UAVs. The differences between FANETs, MANETs (Mobile Ad-hoc Networks) and VANETs (Vehicle Ad-Hoc Networks) are clarified first, and then the main FANET design challenges are introduced. Along with the existing FANET protocols, open research issues are also discussed.

A vision-based formation control framework

Abstract: We describe a framework for cooperative control of a group of nonholonomic mobile robots that allows us to build complex systems from simple controllers and estimators. The resultant modular approach is attractive because of the potential for reusability. Our approach to composition also guarantees stability and convergence in a wide range of tasks. There are two key features in our approach: 1) a paradigm for switching between simple decentralized controllers that allows for changes in formation; 2) the use of information from a single type of sensor, an omnidirectional camera, for all our controllers. We describe estimators that abstract the sensory information at different levels, enabling both decentralized and centralized cooperative control. Our results include numerical simulations and experiments using a testbed consisting of three nonholonomic robots.