Cooperative Localization and Tracking in Distributed Robot-Sensor Networks

This paper addresses the problem of real-time position and orientation estimation of networked mobile robots in two-dimensional Euclidean space with simultaneous tracking of a rigid unknown object based on exteroceptive sensory information extracted from distributed vision systems. The sufficient and necessary conditions for team localization are proposed. A localization and object tracking approach based on statistical operators and graph searching algorithms is presented for a team of robots localized with het- erogeneous sensors. The approach was implemented in an experimental platform consisting of car-like mobile robots equipped with omnidirectional video cameras and IEEE 802.11b wireless networking. The experimental results validate the approach.

Coverage of communication-based sensor nodes deployed location and energy efficient clustering algorithm in WSN

An effective algorithm based on signal coverage of effective communication and local energy-consumption saving strategy is proposed for the application in wireless sensor networks.This algorithm consists of two sub-algorithms.One is the multi-hop partition subspaces clustering algorithm for ensuring local energybalanced consumption ascribed to the deployment from another algorithm of distributed locating deployment based on efficient communication coverage probability（DLD-ECCP）.DLD-ECCP makes use of the characteristics of Markov chain and probabilistic optimization to obtain the optimum topology and number of sensor nodes.Through simulation,the relative data demonstrate the advantages of the proposed approaches on saving hardware resources and energy consumption of networks.

A Dedicated MAC Protocol Package for Real-Time Ocean Current Field Estimation Using Distributed Underwater Acoustic Sensor Networks

Distributed underwater acoustic sensor networks(UASNs)are envisioned in real-time ocean current velocity estimation.However,UASNs at present are still dominated by post-processing partially due to the complexity of on-line detection for travel times and lack of dedicated medium access control(MAC)protocols.In this study,we propose a dedicated MAC protocol package for real-time ocean current velocity estimation using distributed UASNs.First,we introduce the process and requirements of ocean current velocity estimation.Then,we present a series of spatial reuse time division multiple access(TDMA)protocols for each phase of real-time ocean current field estimation using distributed UASNs,followed by numerical analysis.We divide UASNs into two categories according to their computing ability:feature-complete and feature-incomplete systems.The feature-complete systems that have abundant computing ability carry out the presented MAC protocol package in three phases,whereas the feature-incomplete ones do not have enough computing ability and the presented MAC protocol package is reduced to two phases plus an additional downloading phase.Numerical analysis shows that feature-complete systems using mini-slot TDMA have the best real-time performance,in comparison with feature-incomplete systems and other feature-complete counterparts.Feature-incomplete systems are more energy-saving than feature-complete ones,owing to the absence of in-network data exchange.

Ethernet based time synchronization for Raspberry Pi network improving network model verification for distributed active turbulent flow control

Friction drag primarily determines the total drag of transport systems. A promising approach to reduce drag at high Reynolds numbers(> 104) are active transversal surface waves in combination with passive methods like a riblet surface. For the application in transportation systems with large surfaces such as airplanes, ships or trains, a large scale distributed real-time actuator and sensor network is required. This network is responsible for providing connections between a global flow control and distributed actuators and sensors. For the development of this network we established at first a small scale network model based on Simulink and True Time. To determine timescales for network events on different package sizes we set up a Raspberry Pi based testbed as a physical representation of our first model. These timescales are reduced to time differences between the deterministic network events to verify the behavior of our model. Experimental results were improved by synchronizing the testbed with sufficient precision. With this approach we assure a link between the large scale model and the later constructed microcontroller based real-time actuator and sensor network for distributed active turbulent flow control.