Network surveillance systems provide extended perception and distributed sensing capability in monitored environments through real time monitoring of the target area and target objects using multiple networked sensors. The development of wireless communication and sensing technology make it possible to deploy networked surveillance systems in various environments. We consider a surveillance network where the sensors are static. The task of tracking targets in a surveillance network is challenging because of the following reasons: (1) the location of the sensors need to be optimally deployed. (2) The view of the sensors need to be optimized so that at a given time the targets are shown with a discernable resolution for feature identification. (3) It is important to devise stable control algorithms for accomplishing the surveillance task. When the target moves, it is important to switch the sensing task between sensors to maintain the visibility of the target with adequate resolution. This paper presents a novel method to deploy static sensors given a target region and a dynamic programming method to optimally switch sensors when the target moves. Finally, simulation results demonstrate the efficacy of the proposed approach for tracking targets over an area.

The task of visual surveillance involves pervasively observing multiple targets as they move through a field of sensor nodes. Mutational analysis and shape based control have been proposed to overcome the limitations of current feature (point) based visual servoing and tracking techniques generally employed to provide an optimal solution for the surveillance task. Hausdorff tracking paradigm for visual tracking of multiple targets using a single sensor has been proposed for accomplishing the surveillance task. However, Hausdorff tracking incorporates some redundancy in the actuation mechanism. This paper exploits this redundancy in the camera motion in order to accomplish various sub-tasks which can be assigned to the system, such as minimization of consumed energy maintaining manipulability etc. The complete task can then be expressed in a multi-objective constrained optimization framework and can be solved, i.e., the input to the camera can be derived, using various methods such as physical programming, nonlinear programming, weighted sum method, etc. In this paper, we use the physical programming method based on the various advantages such as ease of expressing multiple objectives in a physically significant manner. Experimental results are provided which show the advantages of using the physical programming approach over the weighted sum method for constructing the task criterion for multi-objective optimization problems.

A distributed processing and communication approach is applied to networked surveillance systems providing an extended perception and sensing capability in monitored environments. By pervasive we mean that the entire surveyed area is covered by a heterogeneous collection of fixed and mobile sensors. The sensor network uses a cooperative tracking technique that allows for the deployment of mobile sensors based on data provided by other sensors in the network. Also, an image-based tracking technique is used for tracking when the target is in view. The task of tracking multiple targets in a distributed surveillance network is a challenging problem because of the following reasons: (1) multiple targets need to be monitored and tracked continuously and must remain in view of at least one of the sensors; (2) the view of the sensors needs to be optimized so that the targets are observed with a discernible resolution for feature identification; (3) it is important to devise stable control algorithms for accomplishing the surveillance task; (4) assigning tracking tasks to sensors must consider load balancing and efficient use of all sensors. This paper presents a distributed communication and processing model that allows for a fast deployment of sensor nodes and implementation of ad hoc tracking in a multi-target surveillance scenario. Also, experimental results demonstrate the efficacy of the proposed approach for tracking multiple targets over a large area with fixed and mobile sensors

Pervasive surveillance can be defined as continuous monitoring and tracking of multiple targets in a large monitored region so that they do not leave the field of view (FOV) of the sensors observing them. Despite the limited sensing capability and range of the individual sensors, the surveillance network can track targets over a large region based on transferring the target tracking task. The challenge for such large scale networked systems is to design an efficient and scalable modeling and analysis tool and devise stable control algorithms for accomplishing the surveillance task. Mutational analysis and shape based control have been proposed to overcome the limitations of current feature (point) based visual servoing techniques, however, they fail to capture the discrete switching nature of the surveillance task of tracking the target using multiple sensors. This paper presents a mutational hybrid model for such pervasive surveillance networks which retains the advantages of using mutational equations while also being able to model the discrete switching between various sensors. We also present an example pervasive surveillance scenario modeled using the proposed method and experimental results verifying the proposed approach. © 2006 IEEE.

For Internet based real-time teleoperation systems, random time delay can cause instability in the closed loop control system and hence hinder task accomplishment. Event based control systems have been proposed to overcome the instability caused by the random time delay. High latency at the transport layer can still impede effective and reliable execution of tasks with high dexterity requirements. Network QoS based dynamic resource allocation has been proposed to increase the efficiency and reliability of task execution. However, these approaches only try to mitigate or overcome the effects of random time delay and do not address the cause of latency issues in the communication channel. This paper addresses the efficiency and reliability requirements for supermedia enhanced teleoperated systems by reducing the end-to-end transmission latency through the use of overlay networks. The proposed system reduces the transmission latency by using multiple, disjoint paths in overlay networks. The proposed system facilitates reliable and efficient task completion for tasks with high dexterity requirements. Experimental validation of the proposed teleoperated system using the PlanetLab Network is provided for the task of teleoperating a mobile manipulator system.

In supermedia enhanced Internet based teleoperation systems, the data flowing between the operator and the robot include robotic control commands, video, audio, haptic feedback and other media types. The difference between an Internet based teleoperation system and other Internet applications are that (1) there are many media types involved in teleoperation systems and each of them has a particular quality of service (QoS) requirement; and (2) some media types are very latency sensitive. Overlay networks have been proposed to improve the QoS of teleoperation applications. However efficient use the overlay network resources and the distribution of these resources optimally to all supermedia streams remains an important problem. This paper aims to provide a framework of QoS management for teleoperation systems over overlay networks. The validity and performance of the system is evaluated using the PlanetLab overlay network.

Networked surveillance systems provide an extended perception and distributed reasoning capability in monitored environments through the use of multiple networked sensors. The challenge for such large scale networked systems is to design an efficient modeling and analysis tool and devise stable control algorithms for accomplishing the surveillance task. Current feature (point) based visual servo and tracking techniques generally employed do not provide an optimal solution for the surveillance task. This paper presents a mutational analysis approach for shapes, and shape based control to model and design mechanisms for such active surveillance systems. The techniques of image based Hausdorff tracking and cooperative Hausdorff tracking are introduced. Finally, experimental results demonstrate the efficacy of the proposed approach for tracking targets over a large area.

Robots are developed to perform myriad kinds of complex tasks. To enhance the system performance, tasks should be optimally distributed among robots or subsystems of a single robot. Applied to mobile manipulators, optimal task distribution can be obtained by implementing an optimal redundancy resolution approach. A lot of work has been done in this area with a priori-specified tasks. However, for tele-operated mobile manipulator systems, tasks are generated on-line by the operator, and task requirements vary significantly and are not known a priori. This renders static task distribution schemes unsuitable for achieving optimal performance and mandates the use of online modification of optimal task distribution algorithms. This paper proposes a new optimal task distribution method for tele-operated mobile manipulators. In this method, task dexterity indices, which describe the task requirements are generated online. Based on these indices, the criterion function for optimal performance is constructed using physical programming. The solution obtained by this algorithm is more suitable for varying tasks, and has a better defined physical meaning. The effectiveness of the proposed method is verified by experimental results.

The coordination of multi-robots is required in many scenarios for efficiency and task completion. Combined with teleoperation capabilities, coordinating robots provide a powerful tool. Add to this the Internet and now it is possible for multi-experts at multi-remote sites to control multi-robots in a coordinated fashion. For this to be feasible there are several hurdles to be crossed including Internet type delays, uncertainties in the environment and uncertainties in the object manipulated. In addition, there is a need to measure and control the quality of tele-coordination. This paper proposes a measure for the quality of tele-coordination, referred to as the coordination index, and details the design procedure that ensures a system performs at a required index. The theory developed was tested by bilaterally tele-coordinating two mobile manipulators via the Internet. The experimental results confirmed the theory presented.

This paper presents an analysis and design method for human/robot integrated systems, especially fro the coordination of human and robot formations based on a group of distributed mobile manipulators. The key for the human/robot integrated system is to create a common motion reference that can be understood by both human and the robots in the formation. First, the perceptive reference frame is introduced and the characteristics of perceptive frame are compared with time based reference frame. Next, the stability of the system based on perceptive reference frame is investigated. The applications of perceptive reference frame to multi-agents coordination in a formation, human/mobile manipulators coordination are then discussed. Based on the perceptive reference frame, the human can be naturally integrated into the robot formation. Human intelligence can therefore be integrated with the mobility and dexterous manipulation capability of the mobile manipulators to undertake complex tasks. The robot formation is therefore able to reconfigure and thus cope with unexpected events. Experiments have been used to verify the theoretical results.

In order to execute complicated tasks involving contact with the environment, the robot manipulator must have force control capabilities. Many strategies for performing constrained motion control have been developed. The major drawback of these strategies is that they can only provide for the control of the interaction forces along fixed task space directions. However, many applications necessitate interaction force control along arbitrary and changing directions. In this paper, a new hybrid force/position controller, implemented in a moving reference frame, which can control the interaction force along arbitrary directions is proposed. Using the proposed controller the robot manipulator can interact with workpieces whose shape is not pre-specified. Thus tasks like milling, deburring, polishing and surface tracking, that involve constrained motion control of the robot manipulator can be performed on a wide variety of workpieces without explicit knowledge of the shape of the workpiece. The design of this new hybrid force/position controller, implemented in the moving hand coordinate frame, is presented and the controller is shown to be stable. Simulation studies for the task of tracking unknown surfaces are also presented.