Logical sensor systems

Journal ArticleMulti-sensor systems require a coherent and efficient treatment of the information provided by the various sensors. We propose a framework the Logical Sensor Specification System, in which the sensors can be abstractly defined in terms of computational processes operating on the output from other sensors. Various properties of such an organization are investigated, and a particular implementation is described

A fault tolerant sensor scheme

Journal ArticleMulti-sensor systems pose the problem of how to coherently and efficiently treat the data provided by the various sensors. However. the availability of greater numbers of sensors also broadens the ability to build fault tolerant sensor systems. We define a framework in which sensors can be abstractly defined in terms of computational processes operating on the output from other sensors. Such processes are called logical sensors. Logical sensors make sensor configuration and integration easier and facilitate reconfiguration of senor systems to that fault tolerance can be both expressed and achieved

Adaptive Synchronization of Robotic Sensor Networks

The main focus of recent time synchronization research is developing power-efficient synchronization methods that meet pre-defined accuracy requirements. However, an aspect that has been often overlooked is the high dynamics of the network topology due to the mobility of the nodes. Employing existing flooding-based and peer-to-peer synchronization methods, are networked robots still be able to adapt themselves and self-adjust their logical clocks under mobile network dynamics? In this paper, we present the application and the evaluation of the existing synchronization methods on robotic sensor networks. We show through simulations that Adaptive Value Tracking synchronization is robust and efficient under mobility. Hence, deducing the time synchronization problem in robotic sensor networks into a dynamic value searching problem is preferable to existing synchronization methods in the literature.Comment: First International Workshop on Robotic Sensor Networks part of Cyber-Physical Systems Week, Berlin, Germany, 14 April 201

Instrumented sensor system - practice

technical reportIn previous work, we introduced the notion of Instrumented Logical Sensor Systems (ILSS) that are derived from a modeling and design methodology [4, 2]. The instrumented sensor approach is based on a sensori-computational model which defines the components of the sensor system in terms of their functionality, accuracy, robustness and efficiency. This approach provides a uniform specification language to define sensor systems as a composition of smaller, predefined components. From a software engineering standpoint, this addresses the issues of modularity, reusability, and reliability for building complex multisensor systems. In this report, we demonstrate the practicality of this approach and discuss several design and implementation aspects in the context of mobile robot applications

Instrumented sensor system architecture

Journal ArticleSensor systems are becoming ubiquitous throughout society, yet their design, construction and operation are still more of an art than a science. In this paper, we define, develop, and apply a formal semantics for sensor systems that provides a theoretical framework for an integrated software architecture for modeling sensor-based control systems. Our goal is to develop a design framework which allows the user to model, analyze and experiment with different versions of a sensor system. This includes the ability to build and modify multisensor systems and to monitor and debug both the output of the system and the affect of any modification in terms of robustness, efficiency, and error measures. The notion of Instrumented Logical Sensor Systems (ILSS) that are derived from this modeling and design methodology is introduced. The instrumented sensor approach is based on a sensori-computational model which defines the components of the sensor system in terms of their functionality, accuracy, robustness and efficiency. This approach provides a uniform specification language to define sensor systems as a composition of smaller, predefined components. From a software engineering standpoint, this addresses the issues of modularity, reusability, and reliability for building complex systems. An example is given which compares vision and sonar techniques for the recovery of wall pose

A learning controller for nonrepetitive robotic operation

A practical learning control system is described which is applicable to complex robotic and telerobotic systems involving multiple feedback sensors and multiple command variables. In the controller, the learning algorithm is used to learn to reproduce the nonlinear relationship between the sensor outputs and the system command variables over particular regions of the system state space, rather than learning the actuator commands required to perform a specific task. The learned information is used to predict the command signals required to produce desired changes in the sensor outputs. The desired sensor output changes may result from automatic trajectory planning or may be derived from interactive input from a human operator. The learning controller requires no a priori knowledge of the relationships between the sensor outputs and the command variables. The algorithm is well suited for real time implementation, requiring only fixed point addition and logical operations. The results of learning experiments using a General Electric P-5 manipulator interfaced to a VAX-11/730 computer are presented. These experiments involved interactive operator control, via joysticks, of the position and orientation of an object in the field of view of a video camera mounted on the end of the robot arm

Multisensor knowledge systems

technical reportWe describe an approach which facilitates and makes explicit the organization of the knowledge necessary to map multisensor system requirements onto an appropriate assembly of algorithms, processors, sensors, and actuators. We have previously introduced the Multisensor Kernel System and Logical Sensor Specifications as a means for high-level specification of multisensor systems. The main goals of such a characterization are: to develop a coherent treatment of multisensor information, to allow system reconfiguration for both fault tolerance and dynamic response to environmental conditions, and to permit the explicit description of control. In this paper we show how Logical Sensors can be incorporated into an object-based approach to the organization of multisensor systems. In particular, we discuss: * a multisensor knowledge base, * a sensor specification scheme, and * a multisensor simulation environment. We give an example application of the system to CAD-based 2-D vision

Robust Sensor Fusion Algorithms: Calibration and Cost Minimization.

A system reacting to its environment requires sensor input to model the environment. Unfortunately, sensors are electromechanical devices subject to physical limitations. It is challenging for a system to robustly evaluate sensor data which is of questionable accuracy and dependability. Sensor fusion addresses this problem by taking inputs from several sensors and merging the individual sensor readings into a single logical reading. The use of heterogeneous physical sensors allows a logical sensor to be less sensitive to the limitations of any single sensor technology, and the use of multiple identical sensors allows the system to tolerate failures of some of its component physical sensors. These are examples of fault masking, or N-modular redundancy. This research resolves two problems of fault masking systems: the automatic calibration of systems which return partially redundant image data is problematic, and the cost incurred by installing redundant system components can be prohibitive. Both are presented in mathematical terms as optimization problems. To combine inputs from multiple independent sensors, readings must be registered to a common coordinate system. This problem is complex when functions equating the readings are not known a priori. It is even more difficult in the case of sensor readings, where data contains noise and may have a sizable periodic component. A practical method must find a near optimal answer in the presence of large amounts of noise. The first part of this research derives a computational scheme capable of registering partially overlapping noisy sensor readings. Another problem with redundant systems is the cost incurred by redundancy. The trade-off between reliability and system cost is most evident in fault-tolerant systems. Given several component types with known dependability statistics, it is possible to determine the combinations of components which fulfill dependability constraints by modeling the system using Markov chains. When unit costs are known, it is desirable to use low cost combinations of components to fulfill the reliability constraints. The second part of this dissertation develops a methodology for designing sensor systems, with redundant components, which satisfy dependability constraints at near minimal cost. Open problems are also listed

Collaborative wireless sensor networks in industrial and business processes

Wireless Sensor Networks (WSNs) create the technological basis for building pervasive, large-scale distributed systems, which can sense their environment in great detail, communicate the relevant information via the wireless medium, reason collectively upon the observed situation and react according to the application-specific goals. Embedding sensing, processing and communication in one tiny device (the sensor node or simply mote), which can subsequently collaborate with peers and build a self-organizing, self-healing network, stimulates a long list of applications from various domains, ranging from environmental monitoring to industrial processes, and even further to cognitive robotic systems or space exploration. At first glance the complexity of such applications is overwhelming, given the serious resource limitations of sensor nodes, in terms of computational power, storage space, radio performance and battery power. However, WSNs have a unique feature that balances the inherent resource limitations: the ability of in-network collaboration at scale. Through collaboration WSNs can organize efficiently, prolong system lifetime, handle dynamics, detect and correct errors, all with the final goal of eventually executing reliably the user application. Following this line, researchers devised an impressive number of collaborative WSN algorithms and protocols in recent years. Significant progress has also been made on the market side, so that nowadays we can claim that WSNs are no longer just lab prototypes. Standardization initiatives (such as IEEE 802.15.4) are being put into practice and the general industry trend strongly suggests that the epoch of pioneering research in building and experimenting with “motes” is approaching an end. It is now the logical time for system integration and for creating bridges to connected fields. This thesis focuses on WSN integration in industrial and business processes, and, more specifically, on exploring collaborative techniques to make WSNs more reliable, intelligent, effective and easy-to-use in industry-related scenarios