Modeling and Analysis of Beaconless and Beacon-Based Policies for a Swarm-Intelligent Inspection System

We are developing a swarm-intelligent inspection system based on a swarm of autonomous, miniature robots, using only on-board, local sensors. To estimate intrinsic advantages and limitations of the proposed possible distributed control solution, we capture the dynamic of the system at a higher abstraction level using non-spatial probabilistic microscopic and macroscopic models. In a previous publication, we showed that we are able to predict quantitatively the performances of the swarm of robots for a given metric and a beaconless policy. In this paper, after briefly reviewing our modeling methodology, we explore the effect of adding an additional state to the individual robot controller, which allow robots to serve as a beacon for teammates and therefore bias their inspection routes. Results show that this additional complexity helps the swarm of robots to be more efficient in terms of energy consumption but not necessarily in terms of time required to complete the inspection. We also demonstrate that a beacon-based policy introduces a strong coupling among the behavior of robots, coupling which in turn results in nonlinearities at the macroscopic model level

Multi-robot Boundary Coverage with Plan Revision

This paper revisits the multi-robot boundary coverage problem in which a group of k robots must inspect every point on the boundary of a 2-dimensional environment. We focus on the case in which revision of the original inspection plan may be necessary due to changes in the robot team size or the environment. Building upon prior work, which presented a graph-based approach to path planning for this problem, we present a graph representation of the task that is greatly reduced in complexity and a path revision algorithm appropriate for addressing such changes

Coordination schemes for distributed boundary coverage with a swarm of miniature robots:synthesis, analysis and experimental validation

We provide a comparison of a series of original coordination mechanisms for the distributed boundary coverage problem with a swarm of miniature robots. Our analysis is based on real robot experimentation and models at different levels of abstraction. Distributed boundary coverage is an instance of the distributed coverage problem and has applications such as inspection of structures, de-mining, cleaning, and painting. Coverage is a particularly good example for the benefits of a multi-robot approach due to the potential for parallel task execution and additional robustness out of redundancy. The constraints imposed by a potential application, the autonomous inspection of a jet turbine engine, were our motivation for the algorithms considered in this thesis. Thus, there is particular emphasis on how algorithms perform under the influence of sensor and actuator noise, limited computational and communication capabilities, as well as on the policies about how to cope with such problems. The algorithms developed in this dissertation can be classified into reactive and deliberative algorithms, as well as non-collaborative and collaborative algorithms. The performance of these algorithms ranges from very low to very high, corresponding to highly redundant coverage to near-optimal partitioning of the environments, respectively. At the same time, requirements and assumptions on the robotic platform and the environment (from no communication to global communication, and from no localization to global localization) are incrementally raised. All the algorithms are robust to sensor and actuator noise and gracefully decay to the performance of a randomized algorithm as a function of an increased noise level and/or additional hardware constraints. Although the deliberative algorithms are fully deterministic, the actual performance is probabilistic due to inevitable sensor and actuator noise. For this reason, probabilistic models are used for predicting time to complete coverage and take into account sensor and actuator noise calibrated by using real hardware. For reactive systems with limited memory, the performance is captured using a compact representation based on rate equations that track the expected number of robots in a certain state. As the number of states explode for the deliberative algorithms that require a substantial use of memory, this approach becomes less tractable with the amount of deliberation performed, and we use Discrete Event System (DES) simulation in these cases. Our contribution to the domain of multi-robot systems is three-fold. First, we provide a methodology for system identification and optimal control of a robot swarm using probabilistic models. Second, we develop a series of algorithms for distributed coverage by a team of miniature robots that gracefully decay from a near-optimal performance to the performance of a randomized approach under the influence of sensor and actuator noise. Third, we design an implement a miniature inspection platform based on the miniature robot Alice with ZigBee ready communication capabilities and color vision on a foot-print smaller than 2 × 2 × 3 cm3

Ultra-wideband Localization on Manifolds for Autonomous Metal Structure Inspection

A robot that can probabalistically infer its state and uncertainties while exploiting differential geometry is capable of achieving more consistent, more accurate, robust state estimation. It is being proposed that ultra-wideband, a cutting-edge technology, that is also highly unpredictable, can be used to give autonomy to a magnetic-wheeled crawler robot for the application of metal structure inspection. Thus, ultra-wideband technology is evaluated based on its sensitivity to metal surfaces at varying heights, as well as its response to varying grid sizes between receivers in experiments featuring a Turtlebot and an RTK-GPS. Then, a novel methodology for ultra-wideband grid initialization is presented featuring a simulation of a ship hull with an ultra-wideband grid. Finally, a metal structure is considered as a parallelizable manifold with a bivariate b-spline representation, and the matrix exponential correspondence between a Lie group and its Lie algebra for the Special Orthogonal Group is applied within the Extended Kalman Filter framework. These considerations constitute the Manifold Invariant Extended Kalman Filter (M-IEKF), a novel approach to more robust state estimation. The filter is derived, presented, and evaluated in comparison with a modified standard approach: the Manifold-Constrained Extended Kalman Filter (MC-EKF), which uses zero-noise virtual measurements to constrain the state estimate. Then, for a real proof of concept, an experiment using a magnetic-wheeled crawler robot with ultra-wideband localization on a surface consisting of curved metal plates is carried out giving viability to the approach in the real-world application of autonomous metal structure inspection.M.S

Enhancement of The IEEE 802.15.4 Standard By Energy Efficient Cluster Scheduling

The IEEE 802.15.4 network is gaining popularity due to its wide range of application in Industries and day to day life. Energy Conservation in IEEE 802.15.4 nodes is always a concern for the designers as the life time of a network depends mainly on minimizing the energy consumption in the nodes. In ZigBee cluster-tree network, the existing literature does not provide combined solution for co-channel interference and power efficient scheduling. In addition, the technique that prevents network collision has not been provided. Delay and reliability issues are not addressed in the QoS-aware routing. Congestion is one of the major challenges in IEEE 802.15.4 Network. This network also has issues in admitting real time flows. The aim of the present research is to overcome the issues mentioned above by designing Energy Efficient Cluster Scheduling and Interference Mitigation, QoS Aware Inter-Cluster Routing Protocol and Adaptive Data Rate Control for Clustered Architecture for IEEE 802.15.4 Networks. To overcome the issue of Energy efficiency and network collision energy efficient cluster scheduling and interference mitigation for IEEE 802.15.4 Network is proposed. It uses a time division cluster scheduling technique that offers energy efficiency in the cluster-tree network. In addition, an interference mitigation technique is demonstrated which detects and mitigates the channel interference based on packet-error detection and repeated channel-handoff command transmission. For the issues of delay and reliability in cluster network, QoS aware intercluster routing protocol for IEEE 802.15.4 Networks is proposed. It consists of some modules like reliability module, packet classifier, hello protocol module, routing service module. Using the Packet classifier, the packets are classified into the data and hello packets. The data packets are classified based on the priority. Neighbour table is constructed to maintain the information of neighbour nodes reliabilities by Hello protocol module. Moreover, routing table is built using the routing service module. The delay in the route is controlled by delay metrics, which is a sum of queuing delay and transmission delay. For the issues of congestion and admit real-time flows an Adaptive data rate control for clustered architecture in IEEE 802.15.4 Networks is proposed. A network device is designed to regulate its data rate adaptively using the feedback message i.e. Congestion Notification Field (CNF) in beacon frame received from the receiver side. The network device controls or changes its data rate based on CNF value. Along with this scalability is considered by modifying encoding parameters using Particle Swarm Optimization (PSO) to balance the target output rate for supporting high data rate. Simulation results show that the proposed techniques significantly reduce the energy consumption by 17% and the network collision, enhance the performance, mitigate the effect of congestion, and admit real-time flows

Energy Efficient Routing Algorithms for Wireless Sensor Networks and Performance Evaluation of Quality of Service for IEEE 802.15.4 Networks

The popularity of Wireless Sensor Networks (WSN) have increased tremendously in recent time due to growth in Micro-Electro-Mechanical Systems (MEMS) technology. WSN has the potentiality to connect the physical world with the virtual world by forming a network of sensor nodes. Here, sensor nodes are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the network‘s lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. In this thesis, clustering based routing protocols for WSNs have been discussed. In cluster-based routing, special nodes called cluster heads form a wireless backbone to the sink. Each cluster heads collects data from the sensors belonging to its cluster and forwards it to the sink. In heterogeneous networks, cluster heads have powerful energy devices in contrast to homogeneous networks where all nodes have uniform and limited resource energy. So, it is essential to avoid quick depletion of cluster heads. Hence, the cluster head role rotates, i.e., each node works as a cluster head for a limited period of time. Energy saving in these approaches can be obtained by cluster formation, cluster-head election, data aggregation at the cluster-head nodes to reduce data redundancy and thus save energy. The first part of this thesis discusses methods for clustering to improve energy efficiency of homogeneous WSN. It also proposes Bacterial Foraging Optimization (BFO) as an algorithm for cluster head selection for WSN. The simulation results show improved performance of BFO based optimization in terms of total energy dissipation and no of alive nodes of the network system over LEACH, K-Means and direct methods. IEEE 802.15.4 is the emerging next generation standard designed for low-rate wireless personal area networks (LR-WPAN). The second part of the work reported here in provides performance evaluation of quality of service parameters for WSN based on IEEE 802.15.4 star and mesh topology. The performance studies have been evaluated for varying traffic loads using MANET routing protocol in QualNet 4.5. The data packet delivery ratio, average end-to-end delay, total energy consumption, network lifetime and percentage of time in sleep mode have been used as performance metrics. Simulation results show that DSR (Dynamic Source Routing) performs better than DYMO (Dynamic MANET On-demand) and AODV (Ad–hoc On demand Distance Vector) routing protocol for varying traffic loads rates

Air Force Institute of Technology Research Report 2017

This Research Report presents the FY18 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Actas da 10ª Conferência sobre Redes de Computadores

Universidade do MinhoCCTCCentro AlgoritmiCisco SystemsIEEE Portugal Sectio

Journal of Telecommunications and Information Technology, 2017, nr 1

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